Experimental: Field, Laboratory

Field

They randomly assign subjects (or other sampling units) to either treatment or control groups in order to test claims of causal relationships. Random assignment helps establish the comparability of the treatment and control group, so that any differences between them that emerge after the treatment has been administered plausibly reflect the influence of the treatment rather than pre-existing differences between the groups. The distinguishing characteristics of field experiments are that they are conducted real-world settings and often unobtrusively. This is in contrast to laboratory experiments, which enforce scientific control by testing a hypothesis in the artificial and highly controlled setting of a laboratory. Field experiments have some contextual differences as well from naturally-occurring experiments and quasi-experiments. While naturally-occurring experiments rely on an external force (e.g. a government, nonprofit, etc.) controlling the randomization treatment assignment and implementation, field experiments require researchers to retain control over randomization and implementation. Quasi-experiments occur when treatments are administered as-if randomly (e.g. U.S. Congressional districts where candidates win with slim-margins, weather patterns, natural disasters, etc.).

Field experiments encompass a broad array of experimental designs, each with varying degrees of generality. Some criteria of generality (e.g. authenticity of treatments, participants, contexts, and outcome measures) refer to the contextual similarities between the subjects in the experimental sample and the rest of the population. They are increasingly used in the social sciences to study the effects of policy-related interventions in domains such as health, education, crime, social welfare, and politics.

Characteristics

Under random assignment, outcomes of field experiments are reflective of the real-world because subjects are assigned to groups based on non-deterministic probabilities. Two other core assumptions underlie the ability of the researcher to collect unbiased potential outcomes: excludability and non-interference. The excludability assumption provides that the only relevant causal agent is through the receipt of the treatment. Asymmetries in assignment, administration or measurement of treatment and control groups violate this assumption.

Limitations

There are limitations of and arguments against using field experiments in place of other research designs (e.g. lab experiments, survey experiments, observational studies, etc.). Given that field experiments necessarily take place in a specific geographic and political setting, there is a concern about extrapolating outcomes to formulate a general theory regarding the population of interest. However, researchers have begun to find strategies to effectively generalize causal effects outside of the sample by comparing the environments of the treated population and external population, accessing information from larger sample size, and accounting and modeling for treatment effects heterogeneity within the sample. Others have used covariate blocking techniques to generalize from field experiment populations to external populations.

Noncompliance issues affecting field experiments (both one-sided and two-sided noncompliance) can occur when subjects who are assigned to a certain group never receive their assigned intervention. Other problems to data collection include attrition (where subjects who are treated do not provide outcome data) which, under certain conditions, will bias the collected data. These problems can lead to imprecise data analysis; however, researchers who use field experiments can use statistical methods in calculating useful information even when these difficulties occur.

Using field experiments can also lead to concerns over interference between subjects. When a treated subject or group affects the outcomes of the nontreated group (through conditions like displacement, communication, contagion etc.), nontreated groups might not have an outcome that is the true untreated outcome. A subset of interference is the spillover effect, which occurs when the treatment of treated groups has an effect on neighboring untreated groups.

Participants are randomly allocated to each independent variable group. An example is Milgram’s experiment on obedience or Loftus and Palmer’s car crash study.

Laboratory

A laboratory experiment is an experiment conducted under highly controlled conditions (not necessarily a laboratory), where accurate measurements are possible.

The researcher decides where the experiment will take place, at what time, with which participants, in what circumstances and using a standardized procedure.

  • Strength: It is easier to replicate (i.e. copy) a laboratory experiment. This is because a standardized procedure is used.
  • Strength: They allow for precise control of extraneous and independent variables. This allows a cause and effect relationship to be established.
  • Limitation: The artificiality of the setting may produce unnatural behavior that does not reflect real life, i.e. low ecological validity. This means it would not be possible to generalize the findings to a real life setting.
  • Limitation: Demand characteristics or experimenter effects may bias the results and become confounding variables.

Mechanical observations

Human observation is self-explanatory, using human observers to collect data in the study. Mechanical observation involves using various types of machines to collect the data, which is then interpreted by researchers. With continuing improvements in technology, there are many “mechanical” ways of capturing data in observation studies, however, these new “gadgets” tend to be extremely expensive. The most commonly used and least expensive means of mechanically gathering data in an observation study is a video camera. A video camera offers a much more precise means of collecting data than what can simply be recorded by a human observer.

A number of imaginative methods of mechanical observation and device for making such observations have been developed. One of the most widely known devices of this type is the audiometer, a device used by the A C Nielsen Company to record when radio and television sets are turned on and the stations to which they are tuned. The newest generations of this system uses the Storage Instantaneous Audi-meter. This device automatically stores in electronic memory data on television stations tuned in. Nielsen has a central computer that dials these memories on the telephone twice a day and collects the information from them.

a) Voice pitch meters: measures emotional reactions.

b) Electronic checkout scanners: records purchase behavior.

c) Eye-tracking analysis: while subjects watch the advertisement.

Scaling Techniques: Likert Scale, Semantic Differential Scale

Likert Scale

The Likert scale is a five (or seven) point scale which is used to allow the individual to express how much they agree or disagree with a particular statement.

A Likert scale assumes that the strength/intensity of an attitude is linear, i.e. on a continuum from strongly agree to strongly disagree, and makes the assumption that attitudes can be measured.

Strongly Disagree Disagree Undecided Agree Strongly Agree
1 2 3 4 5

Likert Scales have the advantage that they do not expect a simple yes / no answer from the respondent, but rather allow for degrees of opinion, and even no opinion at all.

Therefore, quantitative data is obtained, which means that the data can be analyzed with relative ease.

Offering anonymity on self-administered questionnaires should further reduce social pressure, and thus may likewise reduce social desirability bias.

Semantic Differential Scale

A semantic differential scale is a survey or questionnaire rating scale that asks people to rate a product, company, brand, or any ‘entity’ within the frames of a multi-point rating option. These survey answering options are grammatically on opposite adjectives at each end. For example, love-hate, satisfied-unsatisfied, and likely to return-unlikely to return with intermediate options in between.

Advantages of semantic differential

  • The semantic differential has outdone the other scales like the Likert scale in vitality, rationality, or authenticity.
  • It has an advantage in terms of language too. There are two polar adjectives for the factor to be measured and a scale connecting both these polar.
  • It is more advantageous than a Likert scale. The researcher declares a statement and expects respondents to either agree or disagree with that.
  • Respondents can express their opinions about the matter in hand more accurately and entirely due to the polar options provided in the semantic differential.
  • In other question types like the Likert scale, respondents have to indicate the level of agreement or disagreement with the mentioned topic. The semantic differential scale offers extremely opposite adjectives on each end of the range. The respondents can precisely explain their feedback that researchers use for making accurate judgments from the survey.

Types

  1. Slider rating scale: Questions that feature a graphical slider give the respondent a more interactive way to answer the semantic differential scale question.
  2. Non-slider rating scale: The non-slider question uses typical radio buttons for a more traditional survey look and feel. Respondents are more used to answering.
  3. Open-ended questions: These questions give the users ample freedom to express their emotions about your organization, products, or services.
  4. Ordering: The ordering questions offer the scope to rate the parameters that the respondents feel are best or worst according to their personal experiences.
  5. Satisfaction rating: The easiest and eye-catchy semantic differential scale questions are the satisfaction rating questions.

Structured and Unstructured Observations Research

Observation may take place in the natural or real life setting or in a laboratory. Observational procedures tend to vary from complete flexibility to the use of pre-coded detailed formal instrument. The observer may himself participate actively in the group he is observing or he may be an observer from outside or his presence may be unknown to the people he is observing.

Structured Observation:

Structured observation consists in a careful definition of categories under which the information is to be recorded, standardization of conditions of observation, and is used mostly in studies designed to provide systematic description or to test causal hypothesis.

The use of structured observational technique presupposes that the investigator knows what aspects of the situation under study are relevant to his research purposes and is in a position therefore to develop a specific plan for making and recording observations before he actually begins the collection of data. Structured observation may be employed in the natural field-setting or a laboratory-setting.

Structured observation, in so far as it is used mainly in studies starting with relatively specific formulation, normally allows for much less freedom of choice with respect to the content of observation than is allowed in unstructured observation. Since the situation and the problem are already explicit, the observer is in a position to set up in advance the categories in terms of which he will analyse the situation.

The categories are clearly defined to provide reliable data on the questions to be asked. Of course, such a definition of categories is the end-product of the researcher’s efforts at trying to solve specific coding problems.

To start with, the researcher may be faced with a large number of categories. It is important that the researcher decides upon an appropriate frame of reference for categorization and trains observers accordingly.

  1. E. Bales has developed a procedural system of categories for recording group interaction. He has proposed 12 standard behavioural categories applicable to a wide range of group situations. Behaviour of any group member is coded in terms of careful definition of each category.

The problem of recording observations during a structured observation. The most commonly used system of recording is one that provides the observer with a number of duplicate sheets containing the list of categories to be coded.

Mechanical recording instruments have been used in some studies. For example, Chapple devised an international chronograph. Helen has developed an audio-introspect meter. Bales and Gerbrands have devised an interactional recorder. All these devices are meant to facilitate recording of observational data according to a specific principle of categorization.

Sound recordings and motion pictures have been used when it is necessary to describe the overall nature of an event or to code certain action of a member in terms of a frame of reference provided by the entire event. Of course, each of these has obvious limitations.

Although such devices as motion pictures, tape-recording and television may be very helpful in affording an overall view of a social event, their use does not by itself solve the problem of gathering data for systematic purposes.

Relevant categories for recording behaviour must be established, time-units decided upon, methods set up for recording as to who initiated an action and who was the target. In sum, if the data are to be useful for research, they must be recorded in terms of such a formal scheme.

This problem is effectively tackled by ensuring some kind of a standardization in the observational instrument. There are, however, some special problems in achieving reliable and valid observations.

These are as follows:

(1) One problem derives from the inadequate definition of the kinds of behaviour that are to be accepted as corresponding to a given concept. For example, if the concept of adjustment was not operationally defined, different observers may be inclined to regard different kinds of behaviour as empirical referents of the concept.

(2) Another factor that may lower the reliability of even a well-trained and skilled observer is the degree of confidence one must have in one’s judgement before marking a given category. For example, observers may assign the same observational items to different categories because they may themselves manifest different tendencies to perceive evidence of a particular behaviour.

(3) The constant error introduced by the observer because of the distortion of his perceptions (for various reasons) is one of the major sources of unreliability.

(4) The load of work can also hamper reliability. The result of overloading is often that the observer cannot record all relevant data and may unwittingly record some aspects rather inadequately, thus, introducing bias.

As was suggested earlier, reliability can be increased by careful training of observers. A well-developed observational procedure can be damaged by differences among different observers or by failure to understand the rules for its use. It is necessary, therefore, that a good period of time be devoted to train the observers.

Such a training entails several phases:

(i) Explanation of purposes and theory in the given study,

(ii) Explanation of categories and the rules for their use,

(iii) Purpose of each category for a theoretic scheme, and

(iv) Practice by observer-trainees, discussion on concrete difficulties and reliability-test of observers.

It should be remembered that all this may not always eliminate the constant bias shared by two or more observers. In such a case, the bias can be minimized by same events.

Lastly, we need to consider the relation of the observer with the observed. The observer must carefully prepare his entry into situation and make sure that all members of the group are willing to accept him. Since usually the observer is conspicuously engaged in recording behaviour, using timing device and other technical aids, it is barely possible to disguise the fact that he is doing research.

Hence, it is all the more important that he obtains the group’s full agreement to the inquiry.

The entry of an observer into the group, however unobtrusive, may introduce a new variable into the situation and this may change the behaviour being observed. For example, in a children’s group, the presence of adult observer may have a great distorting influence.

It is important that some thought is given to ways in which the observer’s presence may influence the outcome of research and to develop the techniques that would reduce this possibility. On the whole, people seem to get used to observers if the behaviour of the observer convinces the subjects that he means no ill.

The participant and the non-participant types of observation. This conceptual typology was introduced to social sciences by Prof. Edward Lindeman. Lindeman was very critical of studies based upon schedules of questions for which the investigator found answers by making inquiries of persons.

Lindeman considered as absurd any attempt to avoid bias by posing questions requiring a simple ‘yes’ or ‘no’ reply in a study dealing not only with the ‘what’ of life but also with the ‘why’ and ‘how’ of life. Lindeman was of the opinion that if one wished to know what the subject was really doing one should watch him and not ask him.

Nels Anderson was a intimate participant in the life of ‘Hobos’, on the road, in lodging houses and in their various activities. The tremendous insight which Anderson developed through such an exercise is amply evidenced in his study entitled ‘The Hobo.’

Participant observation has a reference to the observer sharing to a greater or lesser degree the life of the group he is observing. This sharing may be intermittent but active contacts at close proximity do afford an intimate study of persons.

W.F. Whyte in the course of his study published as ‘The Street Corner Society’ was intimately associated with the various aspects of the activities of members in Cornerville. Paul Cressey in his study entitled ‘Taxi Dance Hall’ employed the technique of participant observation and his investigators became part of the social world of the Taxi Dance Hall to the extent it was possible.

The non-participant observation, in contradistinction, is characterized by a relative lack of participation by the observer in the life of the group that he is observing. In sum, to quote John Madge, “When the heart of the observer is made to beat as the heart of any other member of the group under observation, rather than as that of detached emissary from some distant laboratory, then he has earned the title of participant observer.”

In other words, the participant observation is an attempt to put both observer and observed on the same side by making the observer a member of the group so that he can experience what they experience and work within their frame of reference.

On the contrary, the non-participant observation involves the espousal by the observer of a detached role of the observer and recorder without any attempt on his part to experience through participation that which the observed experience.

Unstructured Observation:

The unstructured observation is diametrically opposed to the structured observation in its ideal-typical formulation. The structured observation is characterized by a careful definition of the units to be observed, information to be recorded, the selection of pertinent data for observation and standardization of conditions of observation.

The unstructured observation represents ideally a contrasting situation in respect of all these.

(a) What should be observed? In highly-structured studies, the well-formulated research-problem or hypotheses clearly point to what data will be most relevant.

But in exploratory studies the observer does not know in advance which aspects of the situation will prove relevant. Since unstructured observation is mostly used as an exploratory technique the observer’s understanding of the situation is likely to change as he goes along.

This, in turn, may call for changes in what he observes. It should be noted that such changes called for in the foci of observation are often desirable. Such shifts in focus according to the exigencies of the situation is a characteristic of unstructured observation.

That is, the unstructured observation is flexible, it allows for changes in focus from time to time if and when reasonable clues or doubts warrant such changes with a view to facilitate taking stock of the new observational items that appear to be pertinent or important at different points in time. The observer is always prepared to draw his clues from unanticipated events in an attitude of alert receptivity.

While no stringent criteria or hard and fast rules can be laid down as to how the observer will go about observing a particular situation it would be helpful, however, to indicate some of the significant aspects that the observer can overlook only at his peril.

(1) The observer should see who the participants are, how many they are and how they are related to one another.

(2) The observer should understand the ‘setting.’ He should know in addition to its overt appearance, the kinds of behaviour it encourages, discourages or prevents and its social characteristics.

(3) The observer should also understand the purpose which has brought the subject-participants together, the nature of the purpose and how the goals of participants are related.

(4) The observer must also understand what the participants do, how, with whom and with what they do it. For example, the observer should know what stimulus initiated the behaviour, what the goal is towards which the behaviour is directed, what are the qualities of the behaviour (duration, intensity, etc.) and what are it consequences?

It should be noted that in a practical situation, it is often not possible to obtain enough clues to allow such a comprehensive description. It may also be that the course of events is too fluid to permit consideration of all dimensions of a social situation or that a certain aspect of an occurrence may be so important as to need the entire attention of the observer.

(b) Recording an observation involves two major considerations, viz:

(i) When should the notes be taken, and

(ii) How the notes should be kept.

The best time for recording is on the spot and during the event. This results in minimizing selective bias and distortions of memory. There are, however, many situations in which note taking on the spot is not feasible because this is likely to affect the naturalness of the situation and create suspicions in minds of the persons being observed.

Constant note taking may also affect the quality of observation, as the observer has to divide his attention between observing and writing. In consequence, during the process, the relevant aspects of the situation may be lost to the eye.

In a situation where on the spot detailed note taking is not possible, the memory of the observer may be too heavily taxed if recording is postponed to the expiry of an observational period. In certain situations, it may also help if the observer retires from an on-going situation for a few minutes every hour to make more detailed notes. It is important that the observer should pen down as soon as possible, after the period of observation, a complete account of everything important in the situation. The facility of recording improves if the observer evolved some kind of indexing system.

(c) Ensuring the accuracy of observation is another important concern of the observer. In situations where for some reasons, immediate recording is not possible, he is likely to find that by the time he sits down to write his observations; his memory does not accurately feed in the relevant details.

In order to check the accuracy and completeness of the record, the observer should, if feasible, compare it with a record made by a tape recording equipment. Of course, this is not always feasible; besides, tape recording captures only the auditory stimuli in the situation.

The next best solution is to have two or more people observe the same event. They can later compare their notes and check bias. This is an excellent way to discover one’s blind spots. Two observations may be qualitatively different; against this, two observers from different backgrounds may be employed to observe the same situation. This is understandably a limited remedy.

It happens quite often that the observer injects an overdose of interpretation into his records. This may adversely affect the validity and reliability of his conclusions. One way out of this is to have two observers record the same vent using the same system. A subsequent comparison, between their records may go some way in detecting the intrusion of interpretation.

The participant observer, by virtue of his typical position, faces formidable difficulties in maintaining baselessness. Such an observer may get involved emotionally with some of the people he is studying. This affects his objectivity.

To gain access to intimate data, the observer may allow himself to be absorbed into particular situation he is studying. But this very factor may make him to accept uncritically the behaviour that he should be trying to explain. This problem can be met mainly by the observer becoming aware of his proneness or tendency to take things for granted. An outsider serving as a check may bring home to the observer his blind spot.

It is also possible to detect blind spots by breaking up or dissecting the perceptual field so the factors that lead it to be seen in a particular way lose much of their force. In other words, by approaching the situation in an analytical way the observer may be able to lessen the distorting influence of certain factors that are likely to lead to bias.

The natural way of seeing the situation is to see the action as one centred around the principal actors. But an inconspicuous person, seemingly very insignificant in the situation, or sometimes even a dead person, may be the real center of the situation (e.g., in ceremonies dealing with the propitiation of the soul of a dead person).

An effective screw to control accuracy in observation and interpretations is for the investigator to establish a sort of relationship with the subjects which makes it possible for him to take them into his confidence about the research.

A participant observer’s situation is likely to create inner conflicts within the investigator. This, in turn, may interfere with objectivity. Should the group being observed be undergoing an emergency of some kind, there is indeed a strong pressure on the observer to become an active participant.

He may have to abandon at least temporarily, his detached position as an observer. But if he does enter into the center of activities of the group, he risks the danger of losing his identity as a scientist. Thus, the participant observer is in a dilemma; resulting either way, in the loss of objectivity.

Rosenfeld suggests that bias arising from inner conflicts may be minimized if one is aware of the conflicts and of the nature of one’s defence.

The final issue relates to the relationship between the observer and the observed. In field observation faulty approach vis-a-vis the subjects may have dire consequences for the inquiry. Since the method is applied in the actual life-sphere of the persons, the observer’s mistakes cannot remain insulated incidents.

The observer must decide before he approaches the potential subjects, whether to reveal the facts that he is a researcher or to enter the situation under some other guise. There are advantages as also disadvantages in both these approaches.

It may for certain reasons seem preferable to make known to the subjects his real role as the researcher. This approach is relatively simple compared to disguised observation. Secondly, it increases substantially one’s opportunity to get information which he would get only very indirectly were he to approach them in disguise.

Thirdly, the open declaration approach does not hold the possibility that his activity will harm any of the people in the situation whereas the disguised observer must consider this possibility seriously.

The obvious disadvantage of a direct approach is that this may make the subjects conscious only to the detriment of naturalness of behaviour the observer wants to observe. The researcher therefore has to weigh carefully the relative gains and losses of these two approaches before employing any one.

Entrance into a community requires a very careful staging. If there are many more than two sides to be approached simultaneously, the issue becomes all the trickier. The observer must be prepared to provide a convincing reason for his presence in the community.

It may sometimes be advisable to let influential persons in the community handle the explanation of the investigator’s work. The observer then must decide upon the degree of his participation in the community, ranging from the bare minimum of answering when addressed, to engaging in some major activity concerning the community life.

Survey: Telephonic Survey, Mail, E-mail, Internet Survey, Social Media and Media Listening

Telephonic Survey

A telephone survey is one of the survey methods used in collecting data either from the general population or from a specific target population. Telephone numbers are utilized by trained interviewers to contact and gather information from possible respondents.

The telephone survey approach is usually utilized when there is a need to collection information via public opinion polling. In other words, phone surveys are ideal for data gathering which takes anyone from the general population as potential.

Advantages of phone-based interviewing

There are several reasons why researchers choose CATI interview methodology over other survey methodologies. Here are just a few:

  • Research can be gathered quickly because phone interviews are immediate and skilled interviewers can complete a lot of surveys in a day of work.
  • Most people have telephones, so you have an ample audience for gathering a representative sample to complete the survey.
  • A telephone interview has a personal touch, so it can lead to valuable brand-building benefits if the interviewer surveys in a professional and skilled way.
  • Telephone interviews can be cost-effective as you can have a higher response rate than web surveys, for example.

Disadvantages of a phone survey

  • Sometimes telephone calls are perceived as telemarketing and thus negatively received by potential respondents. This might influence your response rate.
  • It can be challenging to design an effective phone survey because the questions need to be short and precise for easy comprehension.
  • Timing must be carefully considered. The administrators and supervisors should monitor both the time of the call and the length of the actual interview.

Mail

A mail survey is one in which the postal service, or another mail delivery service, is used to mail the survey materials to sampled survey addresses. What is mailed usually consists of a cover letter, the survey questionnaire, and other materials, such as a postage-paid return envelope, an informational brochure to help legitimize the survey organization, detailed instructions about how to participate in the survey, and/or a noncontingent cash incentive.

Applicability of Mail Surveys

  • The survey’s participants are likely to be concerned or interested in the goals of the research, e.g. improving the quality of the brand.
  • You know or have access to the complete name and home address of the members of your target population.
  • Since it is more challenging to complete a written survey than a verbal survey, your respondents must be able to read and write well. It is also ideal if their educational level is above average.
  • The survey does not have time constraints. Sending and receiving a mail survey can be a month-long process.
  • Instructions in the questionnaire can be easily followed and the questions are simple and can be understood without difficulty.

Advantages of a Mail Survey

  • Administration: For those who will administer and supervise the mail survey, not much of an experience are needed. This type of survey does not oblige the authority to make decisions during high-pressure scenarios. For researchers, they are permitted to curtail sampling errors. They also have the jurisdiction of what the respondents can see on the questionnaire, unlike online surveys where software compatibilities and technical issues are factors on how the survey will be displayed.
  • Convenience: Mail surveys provide convenience to respondents for they can answer the questionnaires at their own pace. Survey participants have the liberty to use as much time needed when answering the survey, which will result to more comprehensive and thorough responses. They can also answer the questionnaire anywhere they want to, as long as they have survey instrument.
  • Honesty: Research shows that participants of a survey give more honest answers compared with other data collection methods. This is because respondents are more comfortable giving their views or opinions through writing.
  • Geographical stratification: A mail survey can specifically target different segments of the population.
  • Cost: Mail surveys need not much of manpower. A man alone can administer the entire survey process. Compared with telephone surveys and face-to-face interviews, the cost in conducting a mail survey is relatively cheaper. This type of survey is optimal of there are large sample size involved. Let us say that the participants are around 40,000. Mailing them is cost-effective than calling them one by one. On estimate, a typical medium-scale mail survey can cost at least $5,000. On the contrary, a telephone survey or a face-to-face interview requires double or triple of your budget for a mail survey.

Disadvantages of a Mail Survey

  • Coverage errors and Response Rates: A mail survey usually generates 3-15% response rate. Having said that, it is not the primary drawback of engaging in this type of survey. The real problem is how to obtain a reliable and complete list of participants from the target population. When failed to do so, this will result to coverage errors. Examples are incomplete mailing lists e.g. excluding members of the family that are temporarily away like college students. Biased results and outdated information are also included in coverage errors.
  • Questionnaire design: Since mail surveys do not offer the opportunity for follow-ups, the questionnaire design can make or break the survey. Questions must be brief, straightforward and accurate.
  • Respondents: Mail surveys are unseemly ineffectual for very young children, disabled or sick persons, to those with language barriers, and marginally literate or illiterate.
  • Administration: Researchers have no control as to whether or not the survey has been completely answered or what will happen to the questionnaire after being mailed.

E-mail

Internet Survey

Over the past decade, the use of online and mobile research methods like online surveys has skyrocketed.  Thanks to technological advances, you can now conduct research for a fraction of the cost and time. This makes collecting data easier than ever and better for everyone.

Advantages

Real-time Access

Respondents’ answers store automatically so you get results at your fingertips in no time. This turns analyzing your results into effortless and immediate action.

Increaed Response Rate

The low cost and overall convenience of online surveys bring in a high response. Respondents get to answer questions on their own schedule at a pace they choose.

Design Flexibility

Surveys can be programmed even if they’re very complex.  Intricate skip patterns and logic can be employed seamlessly.  You can create the layout, questions, and answer choices with no hassle.

Low Cost

Collecting data doesn’t have to break the bank anymore.  There are plenty of websites and platforms that make creating your survey fast and affordable.

Convenience

Respondents answer questions on their own schedule and can even have flexibility with completion time.

Rapid deployment and return times are possible with online surveys that don’t use traditional methods.  And, if you have bad contact information for some respondents, you’ll know it almost immediately.

No Interviewer

Since respondents are not disclosing their answers directly to another person, it is easier for them to open up. Interviewers can also influence responses in some cases.

Disadvantages

No Volunteer

The lack of a trained interviewer to clarify and probe can lead to less reliable data.

Possible Cooperation Problems

Online surveys could be deleted and ignored. People hate feeling poked and if they get annoyed, they just have to click delete.

Limited Sampling and Respondent Availability

Certain populations are less likely to have internet access and to respond to online questionnaires. Drawing samples is harder based on email addresses or website visitations.

Fraud

This is the biggest challenge. If your survey is long and/or confusing you might get fake answers. Since there is less accountability, the chances for people just hitting buttons to finish are high. Check the questions you use carefully.

People often take surveys because they’re promised a reward at the end, resulting in them not accurately contributing to your study.

Social Media and Media Listening

Advantages

Unfiltered opinions: Social listening allows you to be the fly on the wall. With social listening, you can gather consumers’ uninfluenced thoughts and opinions. These thoughts and opinions may be less filtered than what they would share in a survey or interview response, making them more authentic.

Travel back in time: Most social mention tools will store and provide access to data for about 24-30 months. Some tools have the ability to go back even further but at an additional cost. This means that if you start a trending program to compare current conversations to past conversations, you can begin analyzing the information right away and don’t have to wait for multiple data collection periods.

Possibilities within other forms of media: Social listening isn’t limited to text. Images, videos, and emojis often help us better understand what consumers are thinking, saying, and doing better than a more traditional research method would allow. That rich media backed up by commentary text allows us to pick up on key terminology and understand how to communicate back to consumers using their own words.

Disadvantages

No guarantees: The nature of social listening is much different from traditional research, where you ask a question to prompt an answer. There are no guarantees with social listening, and you never know what you will (or will not) find. However, if your area of interest is something included in the broad range of topics discussed online, you should be able to uncover useful information, even if it wasn’t the information you initially anticipated finding.

Social listening insights don’t always stand alone. They often work best as a complement to other information or research. However, social listening can add a unique dimension to traditional research, sometimes uncovering the motivation behind behaviors and shedding light on how to move forward.

Types of question: Structured/Close-end, Unstructured/open-end

Structured questions take many forms and include:

  • Single response with nominal or ordinal categories (e.g. From the following list please select the category which includes your household income)
  • Multiple responses (e.g. From the following list of pizza toppings please any or all that you regularly use)
  • Scaled questions (e.g. The President is doing a good job: Strongly Agree to Strongly Disagree), and
  • Numerous variations on these primary types.

Unstructured questions are a bit more qualitative in feel. They do not require pre-defined categories and they allow the respondent to express their views openly. This is their blessing and their curse. Open-ended questions, as they are also known, produce a higher cognitive load in the sense that the respondent has to think harder to come to an answer. This can create a lower response rate and sometimes lesser quality data. On the other hand, they can produce rich insights that provide depth and color to the black and white of structured questions.

Open-ended questions require additional time on the part of the researcher to analyze and code the responses although text-mining software is making this easier. For best results on a survey, keep open-ended questions to a minimum and use them as sub-questions driven by critical responses to a structured question. For example, if someone selects a high or low response to the Net Promoter Score, you can follow up with unstructured questions asking the respondent to elaborate on their score.

Open-ended questions

Open-ended questions are exploratory in nature, and offer the researchers rich, qualitative data. In essence, they provide the researcher with an opportunity to gain insight on all the opinions on a topic they are not familiar with. However, being qualitative in nature makes these types of questions lack the statistical significance needed for conclusive research.

Nevertheless, open-ended questions are incredibly useful in several different ways:

  • Expert interviews
  • Small population studies
  • Preliminary research
  • A respondent outlet
  1. Expert interviews

Since questions that are open-ended ask for the critical thinking and uncut opinion of the respondent, they are perfect for gaining information from specialists in a field that the researcher is less qualified in. Example: If I wanted to learn the history of Ancient China (something I know very little about), I could create my survey for a selected group of historians whose focus is Ancient China. My survey would then be filled with broad open-ended questions that are designed to receive large amounts of content and provide the freedom for the expert to demonstrate their knowledge.

  1. Small population studies

Open-ended questions can be useful for surveys that are targeting a small group of people because there is no need for complex statistical analysis and the qualitative nature of the questions will give you more valuable input from each respondent. The rule here is the group must be small enough for the surveyor to be able to read each unique response and reflect on the information provided. Example: A supervisor who is looking for performance feedback from his/her team of six employees. The supervisor would benefit more from questions that allow the respondents to freely answer rather than forcing them into closed-ended questions that will limit their responses.

  1. Preliminary research

As stated in the closed-ended questions section, conclusive research usually requires preliminary research to be conducted in order to design the appropriate research objects, survey structure and questions. Open-ended questions can reveal to the surveyor a variety of opinions and behaviours among the population that they never realized. It is therefore, incredibly useful to use open-ended questions to gain information for further quantitative research.

  1. A respondent outlet

It is usually a good idea in any survey, no matter how large, to leave an open-ended comments question at the end. This is especially in the case of a survey asking closed-ended questions on attitudes, opinions, or behaviours. Forcing respondents to answer closed-ended questions asks them to fit in your box of options and can leave them with extra information or concerns that they want to share with you. Providing respondents with the outlet of a comment box is showing them the respect they deserve for taking the time to fill out your survey.

There are a few drawbacks to open-ended questions as well. Though respondent answers are almost always richer in quality, the amount of effort it takes to digest the information provided can sometimes be overwhelming. That is why open-ended questions work best in studies with smaller populations. Furthermore, if your survey sample is a fraction of the population you are studying, you will be looking to find data which can be inferred on the overall population as statistically significant. Unfortunately, open-ended questions cannot be used in this manner, as each response should be seen as a unique opinion.

Closed-ended questions

Closed-ended questions come in a multitude of forms, including: multiple choice, drop down, checkboxes, and ranking questions. Each question type doesn’t allow the respondent to provide unique or unanticipated answers, but rather, choose from a list of pre-selected options. It’s like being offered spaghetti or hamburgers for dinner, instead of being asked “What would you like for dinner?”

Use closed-ended questions for the following:

  • When your audience isn’t particularly interested in your survey topic
  • When you need quantifiable data
  • To categorize respondents
  1. When your audience isn’t particularly interested in your survey topic

Closed-ended questions are easier to complete than open-ended questions. Why? Because closed-ended questions lay out all of the possible answers, removing respondents’ task of coming up with their own responses.

So, when you find yourself surveying an audience who may not be excited about what you’re asking them, air on the side of using closed-ended questions. It’ll give them an easier survey-taking experience and, in the process, provide you with a higher completion rate.

  1. When you need quantifiable data

If you’re looking for statistically significant stats, closed-ended questions are the way to go. Going back to our earlier example, using a closed-ended question can help us arrive at stats like: 70% of respondents want to eat spaghetti for dinner versus 30% who prefer hamburgers.

Questions that are closed-ended are conclusive in nature as they are designed to create data that is easily quantifiable. The fact that questions of this type are easy to code makes them particularly useful when trying to prove the statistical significance of a survey’s results. Furthermore, the information gained by closed-ended questions allows researchers to categorize respondents into groups based on the options they have selected.

  1. To categorize respondents

In other words, they allow you to conduct demographic studies. Why is this valuable?

Imagine that the manager of a designer clothing store believes that certain types of people are more likely to visit their store and purchase their clothing than others. To decipher which segment groups are most likely to be their customers, the manager could design a survey for anyone who has been a visitor. This survey could include closed-ended questions on gender, age, employment status, and any other demographic information they’d like to know. Then, it would be followed by questions on how often they visit the store and the amount of money they spend annually. Since all the questions are closed-ended, the store manager could easily quantify the responses and determine the profile of their typical customer. In this case, the manager may learn that her most frequent customers are female students, ages 18-25. This knowledge would allow her to move forward with an action plan on how to cater to this niche better or break into other target demographics.

The major drawback to closed-ended questions is that a researcher must already have a clear understanding of the topic of his/her questions and how they tie into the overall research problem before they are created. Without this, closed-ended questions will lead to insufficient options for respondents to select from, questions that do not properly reflect the research’s purpose, and limited or erroneous information.

For example, if I asked the question, “do you get to work by driving, busing, or walking?” I would have accidentally omitted carpooling, biking, cartwheeling or any other form of transportation I am unaware of. Instead, it would have been better for me to ask the open-ended question of “how do you get to work?” to learn all the different types of answer before forcing the selection based on a list of several options.

Types of question: Structured/Close-end, Unstructured/open-end

Structured questions take many forms and include:

  • Single response with nominal or ordinal categories (e.g. From the following list please select the category which includes your household income)
  • Multiple responses (e.g. From the following list of pizza toppings please any or all that you regularly use)
  • Scaled questions (e.g. The President is doing a good job: Strongly Agree to Strongly Disagree), and
  • Numerous variations on these primary types.

Unstructured questions are a bit more qualitative in feel. They do not require pre-defined categories and they allow the respondent to express their views openly. This is their blessing and their curse. Open-ended questions, as they are also known, produce a higher cognitive load in the sense that the respondent has to think harder to come to an answer. This can create a lower response rate and sometimes lesser quality data. On the other hand, they can produce rich insights that provide depth and color to the black and white of structured questions.

Open-ended questions require additional time on the part of the researcher to analyze and code the responses although text-mining software is making this easier. For best results on a survey, keep open-ended questions to a minimum and use them as sub-questions driven by critical responses to a structured question. For example, if someone selects a high or low response to the Net Promoter Score, you can follow up with unstructured questions asking the respondent to elaborate on their score.

Open-ended questions

Open-ended questions are exploratory in nature, and offer the researchers rich, qualitative data. In essence, they provide the researcher with an opportunity to gain insight on all the opinions on a topic they are not familiar with. However, being qualitative in nature makes these types of questions lack the statistical significance needed for conclusive research.

Nevertheless, open-ended questions are incredibly useful in several different ways:

  • Expert interviews
  • Small population studies
  • Preliminary research
  • A respondent outlet
  1. Expert interviews

Since questions that are open-ended ask for the critical thinking and uncut opinion of the respondent, they are perfect for gaining information from specialists in a field that the researcher is less qualified in. Example: If I wanted to learn the history of Ancient China (something I know very little about), I could create my survey for a selected group of historians whose focus is Ancient China. My survey would then be filled with broad open-ended questions that are designed to receive large amounts of content and provide the freedom for the expert to demonstrate their knowledge.

  1. Small population studies

Open-ended questions can be useful for surveys that are targeting a small group of people because there is no need for complex statistical analysis and the qualitative nature of the questions will give you more valuable input from each respondent. The rule here is the group must be small enough for the surveyor to be able to read each unique response and reflect on the information provided. Example: A supervisor who is looking for performance feedback from his/her team of six employees. The supervisor would benefit more from questions that allow the respondents to freely answer rather than forcing them into closed-ended questions that will limit their responses.

  1. Preliminary research

As stated in the closed-ended questions section, conclusive research usually requires preliminary research to be conducted in order to design the appropriate research objects, survey structure and questions. Open-ended questions can reveal to the surveyor a variety of opinions and behaviours among the population that they never realized. It is therefore, incredibly useful to use open-ended questions to gain information for further quantitative research.

  1. A respondent outlet

It is usually a good idea in any survey, no matter how large, to leave an open-ended comments question at the end. This is especially in the case of a survey asking closed-ended questions on attitudes, opinions, or behaviours. Forcing respondents to answer closed-ended questions asks them to fit in your box of options and can leave them with extra information or concerns that they want to share with you. Providing respondents with the outlet of a comment box is showing them the respect they deserve for taking the time to fill out your survey.

There are a few drawbacks to open-ended questions as well. Though respondent answers are almost always richer in quality, the amount of effort it takes to digest the information provided can sometimes be overwhelming. That is why open-ended questions work best in studies with smaller populations. Furthermore, if your survey sample is a fraction of the population you are studying, you will be looking to find data which can be inferred on the overall population as statistically significant. Unfortunately, open-ended questions cannot be used in this manner, as each response should be seen as a unique opinion.

Closed-ended questions

Closed-ended questions come in a multitude of forms, including: multiple choice, drop down, checkboxes, and ranking questions. Each question type doesn’t allow the respondent to provide unique or unanticipated answers, but rather, choose from a list of pre-selected options. It’s like being offered spaghetti or hamburgers for dinner, instead of being asked “What would you like for dinner?”

Use closed-ended questions for the following:

  • When your audience isn’t particularly interested in your survey topic
  • When you need quantifiable data
  • To categorize respondents
  1. When your audience isn’t particularly interested in your survey topic

Closed-ended questions are easier to complete than open-ended questions. Why? Because closed-ended questions lay out all of the possible answers, removing respondents’ task of coming up with their own responses.

So, when you find yourself surveying an audience who may not be excited about what you’re asking them, air on the side of using closed-ended questions. It’ll give them an easier survey-taking experience and, in the process, provide you with a higher completion rate.

  1. When you need quantifiable data

If you’re looking for statistically significant stats, closed-ended questions are the way to go. Going back to our earlier example, using a closed-ended question can help us arrive at stats like: 70% of respondents want to eat spaghetti for dinner versus 30% who prefer hamburgers.

Questions that are closed-ended are conclusive in nature as they are designed to create data that is easily quantifiable. The fact that questions of this type are easy to code makes them particularly useful when trying to prove the statistical significance of a survey’s results. Furthermore, the information gained by closed-ended questions allows researchers to categorize respondents into groups based on the options they have selected.

  1. To categorize respondents

In other words, they allow you to conduct demographic studies. Why is this valuable?

Imagine that the manager of a designer clothing store believes that certain types of people are more likely to visit their store and purchase their clothing than others. To decipher which segment groups are most likely to be their customers, the manager could design a survey for anyone who has been a visitor. This survey could include closed-ended questions on gender, age, employment status, and any other demographic information they’d like to know. Then, it would be followed by questions on how often they visit the store and the amount of money they spend annually. Since all the questions are closed-ended, the store manager could easily quantify the responses and determine the profile of their typical customer. In this case, the manager may learn that her most frequent customers are female students, ages 18-25. This knowledge would allow her to move forward with an action plan on how to cater to this niche better or break into other target demographics.

The major drawback to closed-ended questions is that a researcher must already have a clear understanding of the topic of his/her questions and how they tie into the overall research problem before they are created. Without this, closed-ended questions will lead to insufficient options for respondents to select from, questions that do not properly reflect the research’s purpose, and limited or erroneous information.

For example, if I asked the question, “do you get to work by driving, busing, or walking?” I would have accidentally omitted carpooling, biking, cartwheeling or any other form of transportation I am unaware of. Instead, it would have been better for me to ask the open-ended question of “how do you get to work?” to learn all the different types of answer before forcing the selection based on a list of several options.

Types of Hypothesis, Sources

Directional Hypothesis

It shows how a researcher is intellectual and committed to a particular outcome. The relationship between the variables can also predict its nature. For example- children aged four years eating proper food over a five-year period are having higher IQ levels than children not having a proper meal. This shows the effect and direction of effect.

Simple Hypothesis

It shows a relationship between one dependent variable and a single independent variable. For example, If you eat more vegetables, you will lose weight faster. Here, eating more vegetables is an independent variable, while losing weight is the dependent variable.

Complex Hypothesis

It shows the relationship between two or more dependent variables and two or more independent variables. Eating more vegetables and fruits leads to weight loss, glowing skin, reduces the risk of many diseases such as heart disease, high blood pressure and some cancers.

Null Hypothesis

It provides the statement which is contrary to the hypothesis. It’s a negative statement, and there is no relationship between independent and dependent variables. The symbol is denoted by “HO”.

Non-directional Hypothesis

It is used when there is no theory involved. It is a statement that a relationship exists between two variables, without predicting the exact nature (direction) of the relationship.

Associative and Causal Hypothesis

Associative hypothesis occurs when there is a change in one variable resulting in a change in the other variable. Whereas, causal hypothesis proposes a cause and effect interaction between two or more variables.

Sources of Hypothesis

  • The resemblance between the phenomenon.
  • Observations from past studies, present-day experiences and from the competitors.
  • Scientific theories.
  • General patterns that influence the thinking process of people.
  1. General Culture in which a Science Develops:

A cultural pattern influences the thinking process of the people and the hypothesis may be formulated to test one or more of these ideas. Cultural values serve to direct research interests. The function of culture has been responsible for developing today’s science to a great dimension. In the words of Goode and Hatt, “to say that the hypotheses are the product of the cultural values does not make them scientifically less important than others, but it does at least indicate that attention has been called to them by the culture itself.

For example, in the Western society race is thought to be an important determinant of human behaviour. Such a proposition can be used to formulate a hypothesis. We may also cite metaphysical bias and metaphysical ideas of Indian culture to have been responsible for the formulation of certain types of hypotheses. It implies that cultural elements of common cultural pattern may form a source of the formulation of hypotheses.

  1. Scientific Theory:

A major source of hypothesis is theory. A theory binds a large body of facts by positing a consistent and lawful relationship among a set of general concepts representing those facts. Further generalizations are formed on the basis of the knowledge of theory. Corollaries are drawn from the theories.

These generalizations or corollaries constitute a part of hypothesis. Since theories deal with abstractions which cannot be directly observed and can only remain in the thought process, a scientific hypothesis which is concerned with observable facts and observable relationship between facts can only be used for the purpose of selecting some of the facts as concrete instances of the concepts and for making a tentative statement about the existence of a relation among the selected facts with the purpose of subjecting the relation to an empirical test.”

A hypothesis emerges as a deduction from theory. Hence, hypotheses become “working instruments of theory” Every worthwhile theory provides for the formulation of additional hypothesis. “The hypothesis is the backbone of all scientific theory construction; without it, confirmation or rejection of theories would be impossible.”

The hypotheses when tested are “either proved or disproved and in turn constitute further tests of the original theory.” Thus the hypothetical type of verbal proposition forms the link between the empirical propositions or facts and the theories. The validity of a theory can be examined only by means of scientific predictions or experimental hypothesis.

  1. Analogies:

Observation of a similarity between two phenomena may be a source of formation of a hypothesis aimed at testing similarity in any other respect. Julian Huxley has pointed out that “casual observation in nature or in the framework of another science may be a fertile source of hypothesis. The success of a system in one discipline can be used in other discipline also. The theory of ecology is based on the observation of certain plants in certain geographical conditions. As such, it remains in the domain of Botany. On the basis of that the hypothesis of human ecology could be conceived.

Hypothesis of social physics is also based on analogy. “When the hypothesis was born out by social observation, the same term was taken into sociology. It has become an important idea in sociological theory”. Although analogy is not always considered, at the time of formulation of hypothesis; it is generally satisfactory when it has some structural analogies to other well established theories. For the systematic simplicity of our knowledge, the analogy of a hypothesis becomes inversely helpful. Formulation of an analogous hypothesis is construed as an achievement because by doing so its interpretation is made easy.

  1. Consequences of Personal, Idiosyncratic Experience as the Sources of Hypothesis:

Not only culture, scientific theory and analogies provide the sources of hypothesis, but also the way in which the individual reacts to each of these is also a factor in the statement of hypotheses. Certain facts are present, but every one of us is not able to observe them and formulate a hypothesis.

Referring to Fleming’s discovery of penicillin, Backrach has maintained that such discovery is possible only when the scientist is prepared to be impressed by the ‘unusual’. An unusual event struck Fleming when he noted that the dish containing bacteria had a green mould and the bacteria were dead. Usually he would have washed the dish and have attempted once again to culture the bacteria.

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But normally, he was moved to bring the live bacteria in close contact with the green mould, resulting in the discovery of penicillin. The example of Sir Issac Newton, the discoverer of the theory of Gravitation, is another glaring example of this type of ‘personal experience’. Although prior to Newton’s observation, several persons had witnessed the falling of the apple, he was the right man to formulate the theory of gravitation on the basis of this phenomenon.

Thus, emergence of a hypothesis is a creative manner. To quote Mc Guigan, “to formulate a useful and valuable hypothesis, a scientist needs first sufficient experience in that area, and second the quality of the genius.” In the field of social sciences, an illustration of individual perspective may be visualized in Veblen’s work. Thorstein Veblen’s own community background was replete with negative experiences concerning the functioning of economy and he was a ‘marginal man’, capable of looking at the capitalist system objectively.

Thus, he could be able to attack the fundamental concepts and postulates of classical economics and in real terms Veblen could experience differently to bear upon the economic world, resulting in the making of a penetrating analysis of our society. Such an excellent contribution of Veblen has, no doubt, influenced social science since those days.

Applied Research

Applied research is a methodology used to solve a specific, practical issue affecting an individual or group. This scientific method of study and research is used in business, medicine, and education in order to find solutions that may improve health, solve scientific problems or develop new technology. Examples of applied research topics will show you how this method can be used to address everyday problems.

Characteristics of Applied Research in Education

  • It clearly highlights generalizations and hypotheses that inform the research findings.
  • It relies on empirical evidence.
  • It is set at providing solutions to a defined problem.
  • It requires accurate observation and description.

Examples of Applied Research

The following are examples for applied research. You can notice that each of these studies aim to resolve a specific and an immediate problem.

  • A study into the ways of improving the levels of customer retention for D-Mart in India.
  • An investigation into the ways of improving employee motivation in Taj Hotel, Mumbai
  • Development of strategies to introduce change in Starbucks global supply-chain management with the view on cost reduction
  • A study into the ways of fostering creative deviance amongst employees without compromising respect for authority.

Types of Applied Research

There are 3 types of applied research. These are evaluation research, research and development, and action research.

  • Evaluation Research

Evaluation research is a type of applied research that analyses existing information about a research subject to arrive at objective research outcomes or reach informed decisions. This type of applied research is mostly applied in business contexts, for example, an organisation may adopt evaluation research to determine how to cut down overhead costs.

  • Research and Development

Research and development is a type of applied research that is focused on developing new products and services based on the needs of target markets. It focuses on gathering information about marketing needs and finding ways to improve on an existing product or create new products that satisfy the identified needs.

  • Action Research

Action research is a type of applied research that is set on providing practical solutions to specific business problems by pointing the business in the right directions. Typically, action research is a process of reflective inquiry that is limited to specific contexts and situational in nature.

Advantages and Disadvantages of Applied Research

The advantages and disadvantages of applied and fundamental research mirror and contrast each other. On the positive side, applied research can be helpful in solving specific problems in business and other settings.

On the negative side, findings of applied research cannot be usually generalized. In other words, applicability of the new knowledge generated as a result of applied research is limited to the research problem. Moreover, applied studies usually have tight deadlines which are not flexible.

Empirical Research

Empirical research is research using empirical evidence. It is also a way of gaining knowledge by means of direct and indirect observation or experience. Empiricism values some research more than other kinds. Empirical evidence (the record of one’s direct observations or experiences) can be analyzed quantitatively or qualitatively. Quantifying the evidence or making sense of it in qualitative form, a researcher can answer empirical questions, which should be clearly defined and answerable with the evidence collected (usually called data). Research design varies by field and by the question being investigated. Many researchers combine qualitative and quantitative forms of analysis to better answer questions which cannot be studied in laboratory settings, particularly in the social sciences and in education.

In some fields, quantitative research may begin with a research question (e.g., “Does listening to vocal music during the learning of a word list have an effect on later memory for these words?”) which is tested through experimentation. Usually, the researcher has a certain theory regarding the topic under investigation. Based on this theory, statements or hypotheses will be proposed (e.g., “Listening to vocal music has a negative effect on learning a word list.”). From these hypotheses, predictions about specific events are derived (e.g., “People who study a word list while listening to vocal music will remember fewer words on a later memory test than people who study a word list in silence.”). These predictions can then be tested with a suitable experiment. Depending on the outcomes of the experiment, the theory on which the hypotheses and predictions were based will be supported or not, or may need to be modified and then subjected to further testing.

Characteristics

  • A research question, which will determine research objectives.
  • A particular and planned design for the research, which will depend on the question and which will find ways of answering it with appropriate use of resources.
  • The gathering of primary data, which is then analysed.
  • A particular methodology for collecting and analysing the data, such as an experiment or survey.
  • The limitation of the data to a particular group, area or time scale, known as a sample: for example, a specific number of employees of a particular company type, or all users of a library over a given time scale. The sample should be somehow representative of a wider population.
  • The ability to recreate the study and test the results. This is known as reliability.
  • The ability to generalise from the findings to a larger sample and to other situations.

Usage

The researcher attempts to describe accurately the interaction between the instrument (or the human senses) and the entity being observed. If instrumentation is involved, the researcher is expected to calibrate his/her instrument by applying it to known standard objects and documenting the results before applying it to unknown objects. In other words, it describes the research that has not taken place before and their results.

In practice, the accumulation of evidence for or against any particular theory involves planned research designs for the collection of empirical data, and academic rigor plays a large part of judging the merits of research design. Several typologies for such designs have been suggested, one of the most popular of which comes from Campbell and Stanley. They are responsible for popularizing the widely cited distinction among pre-experimental, experimental, and quasi-experimental designs and are staunch advocates of the central role of randomized experiments in educational research.

Types and methodologies of empirical research

Empirical research can be conducted and analysed using qualitative or quantitative methods.

  • Quantitative research: Quantitative research methods are used to gather information through numerical data. It is used to quantify opinions, behaviors or other defined variables. These are predetermined and are in a more structured format. Some of the commonly used methods are survey, longitudinal studies, polls, etc
  • Qualitative research: Qualitative research methods are used to gather non numerical data. It is used to find meanings, opinions, or the underlying reasons from its subjects. These methods are unstructured or semi structured. The sample size for such a research is usually small and it is a conversational type of method to provide more insight or in-depth information about the problem Some of the most popular forms of methods are focus groups, experiments, interviews, etc.

Quantitative research methods

Quantitative research methods aid in analyzing the empirical evidence gathered. By using these a researcher can find out if his hypothesis is supported or not.

  • Survey research: Survey research generally involves a large audience to collect a large amount of data. This is a quantitative method having a predetermined set of closed questions which are pretty easy to answer. Because of the simplicity of such a method, high responses are achieved. It is one of the most commonly used methods for all kinds of research in today’s world.
  • Experimental research: In experimental research, an experiment is set up and a hypothesis is tested by creating a situation in which one of the variable is manipulated. This is also used to check cause and effect. It is tested to see what happens to the independent variable if the other one is removed or altered. The process for such a method is usually proposing a hypothesis, experimenting on it, analyzing the findings and reporting the findings to understand if it supports the theory or not.
  • Correlational research: Correlational research is used to find relation between two set of variables. Regression is generally used to predict outcomes of such a method. It can be positive, negative or neutral correlation.
  • Longitudinal study: Longitudinal study is used to understand the traits or behavior of a subject under observation after repeatedly testing the subject over a period of time. Data collected from such a method can be qualitative or quantitative in nature.
  • Cross sectional: Cross sectional study is an observational type of method, in which a set of audience is observed at a given point in time. In this type, the set of people are chosen in a fashion which depicts similarity in all the variables except the one which is being researched. This type does not enable the researcher to establish a cause-and-effect relationship as it is not observed for a continuous time period. It is majorly used by healthcare sector or the retail industry.
  • Causal-Comparative research: This method is based on comparison. It is mainly used to find out cause-effect relationship between two variables or even multiple variables.

Qualitative research methods

Some research questions need to be analysed qualitatively, as quantitative methods are not applicable there. In many cases, in-depth information is needed or a researcher may need to observe a target audience behavior, hence the results needed are in a descriptive form. Qualitative research results will be descriptive rather than predictive. It enables the researcher to build or support theories for future potential quantitative research. In such a situation qualitative research method are used to derive a conclusion to support the theory or hypothesis being studied.

  • Case study: Case study method is used to find more information through carefully analyzing existing cases. It is very often used for business research or to gather empirical evidence for investigation purpose. It is a method to investigate a problem within its real-life context through existing cases. The researcher has to carefully analyse making sure the parameter and variables in the existing case are the same as to the case that is being investigated. Using the findings from the case study, conclusions can be drawn regarding the topic that is being studied.
  • Textual Analysis: This primarily involves the process of describing, interpreting, and understanding textual content. It typically seeks to connect the text to a broader artistic, cultural, political, or social context (Fairclough, 2003).

A relatively new research method, textual analysis is often used nowadays to elaborate on the trends and patterns of media content, especially social media. Data obtained from this approach are primarily used to determine customer buying habits and preferences for product development, and designing marketing campaigns.

  • Focus Groups:

A focus group is a thoroughly planned discussion guided by a moderator and conducted to derive opinions on a designated topic. Essentially a group interview or collective conversation, this method offers a notably meaningful approach to think through particular issues or concerns.

This research method is used when a researcher wants to know the answers to “how,” “what,” and “why” questions. Nowadays, focus groups are among the most widely used methods by consumer product producers for designing and/or improving products that people prefer.

  • Observational method: Observational method is a process to observe and gather data from its target. Since it is a qualitative method it is time consuming and very personal. It can be said that observational method is a part of ethnographic research which is also used to gather empirical evidence. This is usually a qualitative form of research, however in some cases it can be quantitative as well depending on what is being studied.
  • One-on-one interview: Such a method is purely qualitative and one of the most widely used. The reason being it enables a researcher get precise meaningful data if the right questions are asked. It is a conversational method where in-depth data can be gathered depending on where the conversation leads.

Historical, Exploratory, Descriptive, Casual Research

Historical Research

Historical research data is subject to external criticism (verification of genuineness or validity of the source) and internal criticism (exploring the meaning of the source). Historical research has time and place dimensions. Simple chronology is not considered historical research because it does not interpret the meaning of events.

Historical research is a qualitative technique. Historical research studies the meaning of past events in an attempt to interpret the facts and explain the cause of events, and their effect in the present events. In doing so, researchers rely heavily on primary historical data (direct accounts of events, archival data – official documents, personal records, and records of eyewitnesses) and less frequently on secondary historical data.

Advantages

  • The research is not involved in the situation that is studied
  • The researchers do not interact with the subjects of study
  • Analysis of historical data may help explain current and future events

Shortcomings

  • Historical data is incomplete and vulnerable to time (documents can be destroyed by wars or over time)
  • It can also be biased and corrupt (e.g. diaries, letters, etc. are influenced by the person writing them)
  • Historical research is a complex and broad category because the topics of research (e.g. the study of a society) are affected by numerous factors that need to be considered and analysed.

Exploratory Research

Exploratory research is “the preliminary research to clarify the exact nature of the problem to be solved.” It is used to ensure additional research is taken into consideration during an experiment as well as determining research priorities, collecting data and honing in on certain subjects which may be difficult to take note of without exploratory research. It can include techniques, such as:

  • Secondary research, such as reviewing available literature and/or data
  • Informal qualitative approaches, such as discussions with consumers, employees, management or competitors
  • Formal qualitative research through in-depth interviews, focus groups, projective methods, case studies or pilot studies

Advantages

  • Flexibility and adaptability to change
  • Exploratory research is effective in laying the groundwork that will lead to future studies.
  • Exploratory studies can potentially save time and other resources by determining at the earlier stages the types of research that are worth pursuing

Disadvantages

  • Exploratory studies generate qualitative information and interpretation of such type of information is subject to bias
  • These types of studies usually make use of a modest number of samples that may not adequately represent the target population. Accordingly, findings of exploratory research cannot be generalized to a wider population.
  • Findings of such type of studies are not usually useful in decision making in a practical level.

Exploratory research Steps

  • Identify the problem: A researcher identifies the subject of research and the problem is addressed by carrying out multiple methods to answer the questions.
  • Create the hypothesis: When the researcher has found out that there are no prior studies and the problem is not precisely resolved, the researcher will create a hypothesis based on the questions obtained while identifying the problem.
  • Further research: Once the data has been obtained, the researcher will continue his study through descriptive investigation. Qualitative methods are used to further study the subject in detail and find out if the information is true or not.

Descriptive Research

Descriptive research is used to describe characteristics of a population or phenomenon being studied. It does not answer questions about how/when/why the characteristics occurred. Rather it addresses the “what” question (what are the characteristics of the population or situation being studied?). The characteristics used to describe the situation or population are usually some kind of categorical scheme also known as descriptive categories. For example, the periodic table categorizes the elements. Scientists use knowledge about the nature of electrons, protons and neutrons to devise this categorical scheme. We now take for granted the periodic table, yet it took descriptive research to devise it. Descriptive research generally precedes explanatory research. For example, over time the periodic table’s description of the elements allowed scientists to explain chemical reaction and make sound prediction when elements were combined.

Hence, descriptive research cannot describe what caused a situation. Thus, descriptive research cannot be used as the basis of a causal relationship, where one variable affects another. In other words, descriptive research can be said to have a low requirement for internal validity.

The description is used for frequencies, averages and other statistical calculations. Often the best approach, prior to writing descriptive research, is to conduct a survey investigation. Qualitative research often has the aim of description and researchers may follow-up with examinations of why the observations exist and what the implications of the findings are.

Types of Descriptive Research

Descriptive research is classified into different types according to the kind of approach that is used in conducting descriptive research. The different types of descriptive research are highlighted below:

  • Descriptive-survey

Descriptive-survey research uses surveys to gather data about varying subjects. This data aims to know the extent to which different conditions can be obtained among these subjects.

For example, a researcher wants to determine the qualification of employed professionals in Maryland. He uses a survey as his research instrument, and each item on the survey related to qualifications is subjected to a Yes/No answer.

This way, the researcher can describe the qualifications possessed by the employed demographics of this community.

  • Descriptive-normative survey

This is an extension of the descriptive-survey, with the addition being the normative element. In the descriptive-normative survey, the results of the study should be compared with the norm.

For example, an organization that wishes to test the skills of its employees by a team may have them take a skills test. The skills tests are the evaluation tool in this case, and the result of this test is compared with the norm of each role.

If the score of the team is one standard deviation above the mean, it is very satisfactory, if within the mean, satisfactory, and one standard deviation below the mean is unsatisfactory.

  • Descriptive-status

This is a quantitative description technique that seeks to answer questions about real-life situations. For example, a researcher researching the income of the employees in a company, and the relationship with their performance.

A survey will be carried out to gather enough data about the income of the employees, then their performance will be evaluated and compared to their income. This will help determine whether a higher income means better performance and low income means lower performance or vice versa.

  • Descriptive-analysis

Descriptive-analysis method of research describes a subject by further analyzing it, which in this case involves dividing it into 2 parts. For example, the HR personnel of a company that wishes to analyze the job role of each employee of the company may divide the employees into the people that work at the Headquarters in the US and those that work from Oslo, Norway office.

A questionnaire is devised to analyze the job role of employees with similar salaries and work in similar positions.

  • Descriptive classification

This method is employed in biological sciences for the classification of plants and animals. A researcher who wishes to classify the sea animals into different species will collect samples from various search stations, then classify them accordingly.

  • Descriptive-comparative

In descriptive-comparative research, the researcher considers 2 variables which are not manipulated, and establish a formal procedure to conclude that one is better than the other. For example, an examination body wants to determine the better method of conducting tests between paper-based and computer-based tests.

A random sample of potential participants of the test may be asked to use the 2 different methods, and factors like failure rates, time factors, and others will be evaluated to arrive at the best method.

  • Correlative Survey

Correlative used to determine whether the relationship between 2 variables is positive, negative, or neutral. That is, if 2 variables, say X and Y are directly proportional, inversely proportional or are not related to each other.

Characteristics of descriptive research

The term descriptive research then refers to research questions, design of the study, and data analysis conducted on that topic. We call it an observational research method because none of the research study variables are influenced in any capacity.

Some distinctive characteristics of descriptive research are:

  • Quantitative research: Descriptive research is a quantitative research method that attempts to collect quantifiable information for statistical analysis of the population sample. It is a popular market research tool that allows us to collect and describe the demographic segment’s nature.
  • Uncontrolled variables: In descriptive research, none of the variables are influenced in any way. This uses observational methods to conduct the research. Hence, the nature of the variables or their behavior is not in the hands of the researcher.
  • Cross-sectional studies: Descriptive research is generally a cross-sectional study where different sections belonging to the same group are studied.
  • The basis for further research: Researchers further research the data collected and analyzed from descriptive research using different research techniques. The data can also help point towards the types of research methods used for the subsequent research.

Casual Research

Causal research, also called explanatory research, is the investigation of (research into) cause-and-effect relationships. To determine causality, it is important to observe variation in the variable assumed to cause the change in the other variables, and then measure the changes in the other variables. Other confounding influences must be controlled for so they don’t distort the results, either by holding them constant in the experimental creation of data, or by using statistical methods. This type of research is very complex and the researcher can never be completely certain that there are no other factors influencing the causal relationship, especially when dealing with people’s attitudes and motivations. There are often much deeper psychological considerations that even the respondent may not be aware of.

There are two research methods for exploring the cause-and-effect relationship between variables: experimentation (e.g., in a laboratory) and statistical research.

Objectives:

  • Understanding which variables are the cause, and which variables are the effect. For example, let’s say a city council wanted to reduce car accidents on their streets. They might find through preliminary descriptive and exploratory research that both accidents and road rage have been steadily increasing over the past 5 years. Instead of automatically assuming that road rage is the cause of these accidents, it would be important to measure whether the opposite could be true. Maybe road rage increases in light of more accidents due to lane closures and increased traffic. It could also be the case of the old adage “correlation does not guarantee causation.” Maybe both are increasing due to another reason like construction, lack of proper traffic controls, or an influx of new drivers.
  • Determining the nature of the relationship between the causal variables and the effect predicted. Continuing with our example, let’s say the city council proved that road rage had an increasing effect on the number of car accidents in the area. The causal research could be used for two things. First measuring the significance of the effect, like quantifying the percentage increase in accidents that can be contributed by road rage. Second, observing how the relationship between the variables works (i.e., enraged drivers are prone to accelerating dangerously or taking more risks, resulting in more accidents).

Advantages of causal researches

  • Causal research helps identify the causes behind processes taking place in the system. Having this knowledge helps the researcher to take necessary actions to fix the problems or to optimize the outcomes.
  • Causal research provides the benefits of replication if there is a need for it.
  • Causal research helps identify the impacts of changing the processes and existing methods.
  • In causal research, the subjects are selected systematically. Because of this, causal research is helpful for higher levels of internal validity.

Disadvantages of causal research

  • The causal research is difficult to administer because sometimes it is not possible to control the effects of all extraneous variables.
  • Causal research is one of the most expensive research to conduct. The management requires a great deal of money and time to conduct research. Sometimes it costs more than 1 or 2 million dollars to test real-life two advertising campaigns.
  • One disadvantage of causal research is that it provides information about your plans to your competitors. For example, they might use the outcomes of your research to identify what you are up to and enter the market before you.
  • The findings of causal research are always inaccurate because there will always be a few previous causes or hidden causes that will be affecting the outcome of your research. For example, if you are planning to study the performance of a new advertising campaign in an already established market. Then it is difficult for you to do this as you don’t know the advertising campaign solely influences the performance of your business understudy or it is affected by the previous advertising campaigns.
  • The results of your research can be contaminated as there will always be a few people outside your market that might affect the results of your study.
  • Another disadvantage of using causal research is that it takes a long time to conduct this research. The accuracy of the causal research is directly proportional to the time you spend on the research as you are required to spend more time to study the long-term effects of a marketing program.
  • Coincidence in causal research is the biggest flaw of the research. Sometimes, the coincidence between a cause and an effect can be assumed as a cause and effect relationship.
  • You can’t conclude merely depending on the outcomes of the causal research. You are required to conduct other types of research alongside the causal research to confirm its output.
  • Sometimes, it is easy for a researcher to identify that two variables are connected, but to determine which variable is the cause and which variable is the effect is challenging for a researcher.
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