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A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. For example, a study designed to look at the relationship between sleep deprivation and test performance might have a hypothesis that states, “This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived.”

Hypothesis Used in the Scientific Method

In the scientific method, whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment.

The scientific method involves the following steps:

1. Forming a question
2. Performing background research
3. Creating a hypothesis
4. Designing an experiment
5. Collecting data
6. Analyzing the results
7. Drawing conclusions
8. Communicating the results

The hypothesis is what the researchers predict the relationship between two or more variables, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. It is only at this point that researchers begin to develop a testable hypothesis.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Unless you are creating a study that is exploratory in nature, your hypothesis should always explain what you expect to happen during the course of your experiment or research.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore a number of factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment do not support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

Researchers Come up With a Hypothesis

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might for a specific hypothesis that: “People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than are people who have low-stress levels.”

In other instances, researchers might look at commonly held beliefs or folk wisdom. “Birds of a feather flock together” is one example of folk wisdom that a psychologist might try to investigate. The researcher might pose a specific hypothesis that “People tend to select romantic partners who are similar to them in interests and educational level.”

Elements of a Good Hypothesis

When trying to come up with a good hypothesis for your own research or experiments, ask yourself the following questions:

• Is your hypothesis based on your research on a topic?
• Can your hypothesis be tested?
• Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research on your topic. Once you have completed a literature review, start thinking about potential questions you still have.

How to Form a Hypothesis

The first step of a psychological investigation is to identify an area of interest and develop a hypothesis that can then be tested. While a hypothesis is often described as a hunch or a guess, it is actually much more specific. A hypothesis can be defined as an educated guess about the relationship between two or more variables.

For example, a researcher might be interested in the relationship between study habits and test anxiety.

The researcher would propose a hypothesis about how these two variables are related, such as “Test anxiety decreases as a result of effective study habits.”

In order to form a hypothesis, you should take these steps:

• Start by collecting as many observations about something as you can.
• Evaluate these observations and look for possible causes of the problem.
• Create a list of possible explanations that you might want to explore.
• After you have developed some possible hypotheses, it is important to think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

Falsifiability

In the scientific method, falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could also be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that if something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

The Role of Operational Definitions

In the previous example, study habits and test anxiety are the two variables in this imaginary study. A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define exactly what each variable is using what is known as operational definitions. These definitions explain how the variable will be manipulated and measured in the study.

In the previous example, a researcher might operationally define the variable “test anxiety” as the results of a self-report measure of anxiety experienced during an exam. The variable “study habits” might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions of each variable are important because many things can be measured in a number of different ways. One of the basic principles of any type of scientific research is that the results must be replicable. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. How would you operationally define a variable such as aggression? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others. In order to measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming other people. In this situation, the researcher might utilize a simulated task to measure aggressiveness.

Taking Stock of the Industry

Conducting research to better understand the industry your company operates in is integral to success. Knowing who your competition is, who your customers are and what products or services to offer will help you to develop a solid plan. In addition, business research helps organizations avoid future failures. Organizations can determine whether they should expand operations or scale back based on how the industry is doing as a whole. They can even decide if they should apply for a new loan or pay back debts sooner based on current interest rates. Understanding the industry also helps businesses price their products or services effectively, ensuring they are in line with market rates and competitors.

Understanding Your Customers

Your customers are the reason your business exists. As a result, it’s vital to know who they are, how they think, how they feel and why they might need your products or services. Organizations conduct market research in various ways, such as through phone or online surveys, and can also purchase research that has already been published for their industry. It’s a great way to understand what your customers’ biggest challenges are so that you can determine how to help them. Market research is also vital to new product development. Research helps to reduce risk when making a big investment in creating a new product or offering a new service.

Knowing your customers also helps to fine-tune marketing campaigns. This way, you can target customers effectively, really honing in on their pain points and offering your organization as a viable solution. Brand research helps organizations to understand how their customers view them and shows any changes needed to improve the business’ overall image.

Competing Effectively and Efficiently

Every business has some kind of competition; no one operates alone. As a result, it’s important to know who your true competitors are and how you compare. Companies that are honest about their strengths and weaknesses as compared to their competitors have a higher chance of success. Through effective competitor analysis and research, organizations can determine if they need to develop new products or services, whether they should consider new marketing strategies or if their pricing plan needs some tweaks. By understanding the competition better, organizations also can develop new ways to increase market share.

To Remain well-informed

During the process of research, a business would acquire key information related to different areas of the business which the business would analyze, strategize and use the collected business information for improving the efficiency and performance of the business. Reports sent to the top-level management usually have information about the employee preference, consumer likes and dislikes and the different channels that are available effective sales, finance, production, and marketing.

To develop the best strategy

The information so gathered by a business about different areas aids in determining the ideal and best strategy suited to the organization. Say for instance, before initially starting an organization, research helps in evaluating whether the said business if started would be a profitable venture and whether there really exists a demand for the product manufactured by the company. Thus effective research conducted helps in every phase or stages of the business operations by helping in good decision-making.

In ascertaining staff satisfaction level

A clearly carried out research aids in not only uncovering but even in a thorough understanding of the level of staff satisfaction. The management through well-conducted research comes to know of the difficulties experienced by the staff along with getting a clear picture about how to handle the situation at the place of work. Thus it is true that well-conducted research helps the management and the organization in undertaking the needed changes for the efficient, smooth and successful functioning of the organization and in providing satisfaction level to its employees at the workplace. This helps to increase their motivational level as they get coached and trained in their line of need. This helps improve the personal as well as the professional performance of the employees thus improving the overall performance of the organization.

Effective managerial decision-making

By undertaking effective research in different areas, all the areas of the business get thoroughly analyzed and evaluated thus helping in picking up the good techniques for better and more efficient ways that would help in increasing the productivity and profitability of the organization.  In short, it cannot be denied that effective research undertaken provides an answer to all the problems of a business.

The process of collecting data in qualitative research is field-based and iterative, that is, the data collected from the study is organized during analysis in such a way that a pattern will emerge. Unlike quantitative research, it usually starts with the specific and moves toward the general. In this type of research, data patterns generated from analysis inevitably lead to different questions or concepts that the researcher had set prior to data gathering.

Qualitative researchers usually record their thoughts and impressions about the data and methodology that they use. They collect data in different ways and sources, at times using a technique called triangulation in which researchers facilitate validation of data through cross verification from more than two sources.

The main purpose of this kind of research is to understand and interpret social interactions. It usually studies smaller and purposively selected groups of participants. It does not focus on specific variables, but sees the study as a whole. Qualitative research examines the breadth and depth of phenomena. Forms of data gathered typically comprise responses to interviews, participant observations, field notes, reflections, and other open-ended responses, and as such, comprise words, images or objects.

Subjectivity is expected in this research approach as multiple realities are recognized. Researchers and their biases may be known to participants in the research, and participant characteristics may be known to researchers as well. Results in this study are particular, specialized, and therefore less generalizable. Researchers generate new hypotheses and theories from data collected.

Human behavior is viewed by this type of research as dynamic, situational, social and personal. The most common research objectives of qualitative study are to “explore”, “discover”, and “construct”. Qualitative research studies behavior in its natural environment. The final report commonly includes a narrative report with contextual descriptions and direct quotations from research participants.

Assumptions of Qualitative Methods

• Multiple realities are considered in the research which includes views of the researcher, participants of the study, and even the reader of or the audience interpreting the results.
• The researcher actively interacts with the participants and one of his/her goals is to lessen the distance between him/her and the people being studied.
• The researcher recognizes that the research is not value-free, and that it can be influenced by his values and beliefs.
• Qualitative research is context-bound.
• Categories of interest emerge from the participants of the research, rather than set by the researcher before conducting the study. An inductive form of logic is followed.
• The objective of the research is to be able to come up with patterns or theories that will explain the phenomenon being studied.

Quantitative research methods are those methods where a systematic approach is used to collect quantifiable of data by performing computational, mathematical, or statistical techniques. The data collected through quantitative research methods are usually in numerical form.

The proper outcome can be deduced by analyzing the data in a systematic form. The results obtained through quantitative research methods are statistical, logical, and unbiased.

These research methods are applied to a group of the population, which represents the entire population.

Methods like survey research, cross-sectional surveys, longitudinal surveys, correlational research, causal-comparative research, experimental research, are primary data collection methods in quantitative research methods whereas the data collected from methods such as educational institutions, public libraries, data available on internet, government and non-government resources, and commercial information resources, etc. are the secondary data collection methods in quantitative research methods. Click here to learn more about quantitative research methods.

Primary Quantitative Research Methods

There are four different types of quantitative research methods:

Primary quantitative research is the most widely used method of conducting market research. The distinct feature of primary research is that the researcher focuses on collecting data directly rather than depending on data collected from previously done research. Primary quantitative research can be broken down into three further distinctive tracks, as well as the process flow. They are:

A. Techniques and Types of Studies

There are multiple types of primary quantitative research. They can be distinguished into the four following distinctive methods, which are:

1. Survey Research:

Survey Research is the most fundamental tool for all quantitative research methodologies and studies. Surveys used to ask questions to a sample of respondents, using various types such as online polls, online surveys, paper questionnaires, web-intercept surveys, etc. Every small and big organization intends to understand what their customers think about their products and services, how well are new features faring in the market and other such details.

By conducting survey research, an organization can ask multiple survey questions, collect data from a pool of customers, and analyze this collected data to produce numerical results. It is the first step towards collecting data for any research.

This type of research can be conducted with a specific target audience group and also can be conducted across multiple groups along with comparative analysis. A prerequisite for this type of research is that the sample of respondents must have randomly selected members. This way, a researcher can easily maintain the accuracy of the obtained results as a huge variety of respondents will be addressed using random selection. Traditionally, survey research was conducted face-to-face or via phone calls but with the progress made by online mediums such as email or social media, survey research has spread to online mediums as well.

Traditionally, survey research was conducted face-to-face or via phone calls but with the progress made by online mediums such as email or social media, survey research has spread to online mediums as well.

There are two types of surveys, either of which can be chosen based on the time in-hand and the kind of data required: 

Cross-sectional surveys: Cross-sectional surveys are observational surveys conducted in situations where the researcher intends to collect data from a sample of the target population at a given point in time. Researchers can evaluate various variables at a particular time. Data gathered using this type of survey is from people who depict similarity in all variables except the variables which is considered for research. Throughout the survey, this one variable will stay constant.

• Cross-sectional surveys are popular with retail, SMEs, healthcare industries. Information is garnered without modifying any parameters in the variable ecosystem.
• Using cross-sectional survey research method, multiple samples can be analyzed and compared.
• Multiple variables can be evaluated using this type of survey research.
• The only disadvantage of cross-sectional surveys is that the cause-effect relationship of variables cannot be established as it usually evaluates variables at a particular time and not across a continuous time frame.

Longitudinal surveys: Longitudinal surveys are also observational surveys but, unlike cross-sectional surveys, longitudinal surveys are conducted across various time durations to observe a change in respondent behavior and thought-processes. This time can be days, months, years, or even decades. For instance, a researcher planning to analyze the change in buying habits of teenagers over 5 years will conduct longitudinal surveys.

• In cross-sectional surveys, the same variables were evaluated at a given point in time, and in longitudinal surveys, different variables can be analyzed at different intervals of time.
• Longitudinal surveys are extensively used in the field of medicine and applied sciences. Apart from these two fields, they are also used to observe a change in the market trend, analyze customer satisfaction, or gain feedback on products/services.
• In situations where the sequence of events is highly essential, longitudinal surveys are used.
• Researchers say that when there are research subjects that need to be thoroughly inspected before concluding, they rely on longitudinal surveys.

2. Correlational Research:

A comparison between two entities is invariable. Correlation research is conducted to establish a relationship between two closely-knit entities and how one impacts the other and what are the changes that are eventually observed. This research method is carried out to give value to naturally occurring relationships, and a minimum of two different groups are required to conduct this quantitative research method successfully. Without assuming various aspects, a relationship between two groups or entities must be established.

Researchers use this quantitative research method to correlate two or more variables using mathematical analysis methods. Patterns, relationships, and trends between variables are concluded as they exist in their original set up. The impact of one of these variables on the other is observed along with how it changes the relationship between the two variables. Researchers tend to manipulate one of the variables to attain the desired results.

Ideally, it is advised not to make conclusions merely based on correlational research. This is because it is not mandatory that if two variables are in sync that they are interrelated.

Example of Correlational Research Questions:

• • The relationship between stress and depression.
  • The equation between fame and money.
  • The relation between activities in a third-grade class and its students.

3. Causal-Comparative Research:

This research method mainly depends on the factor of comparison. Also called the quasi-experimental research, this quantitative research method is used by researchers to conclude cause-effect equation between two or more variables, where one variable is dependent on the other independent variable. The independent variable is established but not manipulated, and its impact on the dependent variable is observed. These variables or groups must be formed as they exist in the natural set up. As the dependent and independent variables will always exist in a group, it is advised that the conclusions are carefully established by keeping all the factors in mind.

Causal-comparative research is not restricted to the statistical analysis of two variables but extends to analyzing how various variables or groups change under the influence of the same changes. This research is conducted irrespective of the type of relation that exists between two or more variables. Statistical analysis is used to distinctly present the outcome of obtained using this quantitative research method.

Example of Causal-Comparative Research Questions:

• The impact of drugs on a teenager.
• The effect of good education on a freshman.
• The effect of substantial food provision in the villages of Africa.

4. Experimental Research: Also known as true experimentation, this research method is reliant on a theory. Experimental research, as the name suggests, is usually based on one or more theories. This theory has not been proven in the past and is merely a supposition. In experimental research, an analysis is done around proving or disproving the statement. This research method is used in natural sciences.

There can be multiple theories in experimental research. A theory is a statement that can be verified or refuted.

After establishing the statement, efforts are made to understand whether it is valid or invalid. This type of quantitative research method is mainly used in natural or social sciences as there are various statements which need to be proved right or wrong. 

• Traditional research methods are more effective than modern techniques.
• Systematic teaching schedules help children who find it hard to cope up with the course.
• It is a boon to have responsible nursing staff for ailing parents.

1. Research design in case of exploratory research studies: Exploratory research studies are also termed as formulative research studies. The main purpose of such studies is that of formulating a problem for more precise investigation or of developing the working hypotheses from an operational point of view. The major emphasis in such studies is on the discovery of ideas and insights. As such the research design appropriate for such studies must be flexible enough to provide opportunity for considering different aspects of a problem under study. Inbuilt flexibility in research design is needed because the research problem, broadly defined initially, is transformed into one with more precise meaning in exploratory studies, which fact may necessitate changes in the research procedure for gathering relevant data. Generally, the following three methods in the context of research design for such studies are talked about: the survey of concerning literature, the experience survey and the analysis of ‘insight-stimulating’ examples.

The survey of concerning literature happens to be the most simple and fruitful method of formulating precisely the research problem or developing hypothesis. Hypotheses stated by earlier workers may be reviewed and their usefulness be evaluated as a basis for further research. It may also be considered whether the already stated hypotheses suggest new hypothesis. In this way the researcher should review and build upon the work already done by others, but in cases where hypotheses have not yet been formulated, his task is to review the available material for deriving the relevant hypotheses from it.

Besides, the bibliographical survey of studies, already made in one’s area of interest may as well as made by the researcher for precisely formulating the problem. He should also make an attempt to apply concepts and theories developed in different research contexts to the area in which he is himself working. Sometimes the works of creative writers also provide a fertile ground for hypothesis formulation and as such may be looked into by the researcher.

Experience survey means the survey of people who have had practical experience with the problem to be studied. The object of such a survey is to obtain insight into the relationships between variables and new ideas relating to the research problem. For such a survey people who are competent and can contribute new ideas may be carefully selected as respondents to ensure a representation of different types of experience. The respondents so selected may then be interviewed by the investigator. The researcher must prepare an interview schedule for the systematic questioning of informants. But the interview must ensure flexibility in the sense that the respondents should be allowed to raise issues and questions which the investigator has not previously considered. Generally, the experience collecting interview is likely to be long and may last for few hours. Hence, it is often considered desirable to send a copy of the questions to be discussed to the respondents well in advance. This will also give an opportunity to the respondents for doing some advance thinking over the various issues involved so that, at the time of interview, they may be able to contribute effectively. Thus, an experience survey may enable the researcher to define the problem more concisely and help in the formulation of the research hypothesis. This survey may as well provide information about the practical possibilities for doing different types of research.
Analysis of ‘insight-stimulating’ examples is also a fruitful method for suggesting hypotheses for research. It is particularly suitable in areas where there is little experience to serve as a guide. This method consists of the intensive study of selected instances of the phenomenon in which one is interested. For this purpose the existing records, if any, may be examined, the unstructured interviewing may take place, or some other approach may be adopted. Attitude of the investigator, the intensity of the study and the ability of the researcher to draw together diverse information into a unified interpretation are the main features which make this method an appropriate procedure for evoking insights.
Now, what sort of examples are to be selected and studied? There is no clear cut answer to it. Experience indicates that for particular problems certain types of instances are more appropriate than others. One can mention few examples of ‘insight-stimulating’ cases such as the reactions of strangers, the reactions of marginal individuals, the study of individuals who are in transition from one stage to another, the reactions of individuals from different social strata and the like. In general, cases that provide sharp contrasts or have striking features are considered relatively more useful while adopting this method of hypotheses formulation.
Thus, in an exploratory of formulative research study which merely leads to insights or hypotheses, whatever method or research design outlined above is adopted, the only thing essential is that it must continue to remain flexible so that many different facets of a problem may be considered as and when they arise and come to the notice of the researcher.

2. Research design in case of descriptive and diagnostic research studies: Descriptive research studies are those studies which are concerned with describing the characteristics of a particular individual, or of a group, whereas diagnostic research studies determine the frequency with which something occurs or its association with something else. The studies concerning whether certain variables are associated are examples of diagnostic research studies. As against this, studies concerned with specific predictions, with narration of facts and characteristics concerning individual, group or situation are all examples of descriptive research studies. Most of the social research comes under this category. From the point of view of the research design, the descriptive as well as diagnostic studies share common requirements and as such we may group together these two types of research studies. In descriptive as well as in diagnostic studies, the researcher must be able to define clearly, what he wants to measure and must find adequate methods for measuring it along with a clear cut definition of ‘population’ he wants to study. Since the aim is to obtain complete and accurate information in the said studies, the procedure to be used must be carefully planned. The research design mustmake enough provision for protection against bias and must maximise reliability, with due concern for the economical completion of the research study. The design in such studies must be rigid and not flexible and must focus attention on the following:
   • Formulating the objective of the study (what the study is about and why is it being made?)
   • Designing the methods of data collection (what techniques of gathering data will be adopted?)
   • Selecting the sample (how much material will be needed?)
   • Collecting the data (where can the required data be found and with what time period should the data be related?)
   • Processing and analysing the data.
   • Reporting the findings.

In a descriptive/diagnostic study the first step is to specify the objectives with sufficient precision to ensure that the data collected are relevant. If this is not done carefully, the study may not provide the desired information.
Then comes the question of selecting the methods by which the data are to be obtained. In other words, techniques for collecting the information must be devised. Several methods (viz., observation, questionnaires, interviewing, examination of records, etc.), with their merits and limitations, are available for the purpose and the researcher may user one or more of these methods which have been discussed in detail in later chapters. While designing data-collection procedure, adequate safeguards against bias and unreliability must be ensured. Whichever method is selected, questions must be well examined and be made unambiguous; interviewers must be instructed not to express their own opinion; observers must be trained so that they uniformly record a given item of behaviour. It is always desirable to pretest the data collection instruments before they are finally used for the study purposes. In other words, we can say that “structured instruments” are used in such studies.
In most of the descriptive/diagnostic studies the researcher takes out sample(s) and then wishes to make statements about the population on the basis of the sample analysis or analyses. More often than not, sample has to be designed. Different sample designs have been discussed in detail in a separate chapter in this book. Here we may only mention that the problem of designing samples should be tackled in such a fashion that the samples may yield accurate information with a minimum amount of research effort. Usually one or more forms of probability sampling, or what is often described as random sampling, are used.

To obtain data free from errors introduced by those responsible for collecting them, it is necessary to supervise closely the staff of field workers as they collect and record information. Checks may be set up to ensure that the data collecting staff perform their duty honestly and without prejudice. “As data are collected, they should be examined for completeness, comprehensibility, consistency and reliability.”
The data collected must be processed and analysed. This includes steps like coding the interview replies, observations, etc.; tabulating the data; and performing several statistical computations. To the extent possible, the processing and analysing procedure should be planned in detail before actual work is started. This will prove economical in the sense that the researcher may avoid unnecessary labour such as preparing tables for which he later finds he has no use or on the other hand, re-doing some tables because he failed to include relevant data. Coding should be done carefully to avoid error in coding and for this purpose the reliability of coders needs to be checked. Similarly, the accuracy of tabulation may be checked by having a sample of the tables re-done. In case of mechanical tabulation the material (i.e., the collected data or information) must be entered on appropriate cards which is usually done by punching holes corresponding to a given code. The accuracy of punching is to be checked and ensured. Finally, statistical computations are needed and as such averages, percentages and various coefficients must be worked out. Probability and sampling analysis may as well be used. The appropriate statistical operations, along with the use of appropriate tests of significance should be carried out to safeguard the drawing of conclusions concerning the study.
Last of all comes the question of reporting the findings. This is the task of communicating the findings to others and the researcher must do it in an efficient manner. The layout of the report needs to be well planned so that all things relating to the research study may be well presented in simple and effective style.
Thus, the research design in case of descriptive/diagnostic studies is a comparative design throwing light on all points narrated above and must be prepared keeping in view the objective(s) of the study and the resources available. However, it must ensure the minimisation of bias and maximisation of reliability of the evidence collected. The said design can be appropriately referred to as a survey design since it takes into account all the steps involved in a survey concerning a phenomenon to be studied.
The difference between research designs in respect of the above two types of research studies can be conveniently summarised in tabular form as under:

3. Research design in case of hypothesis-testing research studies: Hypothesis-testing research studies (generally known as experimental studies) are those where the researcher tests the hypotheses of causal relationships between variables. Such studies require procedures that will not only reduce bias and increase reliability, but will permit drawing inferences about causality. Usually experiments meet this requirement. Hence, when we talk of research design in such studies, we often mean the design of experiments.
   Professor R.A. Fisher’s name is associated with experimental designs. Beginning of such designs was made by him when he was working at Rothamsted Experimental Station (Centre for Agricultural Research in England). As such the study of experimental designs has its origin in agricultural research. Professor Fisher found that by dividing agricultural fields or plots into different blocks and then by conducting experiments in each of these blocks, whatever information is collected and inferences drawn from them, happens to be more reliable. This fact inspired him to develop certain experimental designs for testing hypotheses concerning scientific investigations. Today, the experimental designs are being used in researches relating to phenomena of several disciplines. Since experimental designs originated in the context of agricultural operations, we still use, though in a technical sense, several terms of agriculture (such as treatment, yield, plot, block etc.) in experimental designs.

Research design is defined as a framework of methods and techniques chosen by a researcher to combine various components of research in a reasonably logical manner so that the research problem is efficiently handled. It provides insights about “how” to conduct research using a particular methodology. Every researcher has a list of research questions which need to be assessed – this can be done with research design.

The sketch of how research should be conducted can be prepared using research design. Hence, the market research study will be carried out on the basis of research design.

The design of a research topic is used to explain the type of research (experimental, survey, correlational, semi-experimental, review) and also its sub-type (experimental design, research problem, and descriptive case-study). There are three main sections of research design: Data collection, measurement, and analysis.

The type of research problem an organization is facing will determine the research design and not vice-versa. Variables, designated tools to gather information, how will the tools be used to collect and analyze data and other factors are decided in research design on the basis of a research technique is decided.

An impactful research design usually creates minimum bias in data and increases trust on the collected and analyzed research information. Research design which produces the least margin of error in experimental research can be touted as the best. The essential elements of research design are:

1. Accurate purpose statement of research design
2. Techniques to be implemented for collecting details for research
3. Method applied for analyzing collected details
4. Type of research methodology
5. Probable objections for research
6. Settings for research study
7. Timeline
8. Measurement of analysis

Research Design Characteristics

Neutrality: The results projected in research design should be free from bias and neutral. Understand opinions about the final evaluated scores and conclusion from multiple individuals and consider those who agree with the derived results.

Reliability: If a research is conducted on a regular basis, the researcher involved expects similar results to be calculated every time. Research design should indicate how the research questions can be formed to ensure the standard of obtained results and this can happen only when the research design is reliable.

Validity: There are multiple measuring tools available for research design but valid measuring tools are those which help a researcher in gauging results according to the objective of research and nothing else. The questionnaire developed from this research design will be then valid.

Generalization: The outcome of research design should be applicable to a population and not just a restricted sample. Generalization is one of the key characteristics of research design.

Types of Research Design

A researcher must have a clear understanding of the various types of research design to select which type of research design to implement for a study. Research design can be broadly classified into quantitative and qualitative research design.

Qualitative Research Design: Qualitative research is implemented in cases where a relationship between collected data and observation is established on the basis of mathematical calculations. Theories related to a naturally existing phenomenon can be proved or disproved using mathematical calculations. Researchers rely on qualitative research design where they are expected to conclude “why” a particular theory exists along with “what” respondents have to say about it.

Quantitative Research Design: Quantitative research is implemented in cases where it is important for a researcher to have statistical conclusions to collect actionable insights. Numbers provide a better perspective to make important business decisions. Quantitative research design is important for the growth of any organization because any conclusion drawn on the basis of numbers and analysis will only prove to be effective for the business. 

Further, research design can be divided into five types:

1. Descriptive Research Design:In a descriptive research design, a researcher is solely interested in describing the situation or case under his/her research study. It is a theory-based research design which is created by gather, analyze and presents collected data. By implementing an in-depth research design such as this, a researcher can provide insights into the why and how of research.
2. Experimental Research Design:Experimental research design is used to establish a relationship between the cause and effect of a situation. It is a causal research design where the effect caused by the independent variable on the dependent variable is observed. For example, the effect of an independent variable such as price on a dependent variable such as customer satisfaction or brand loyalty is monitored. It is a highly practical research design method as it contributes towards solving a problem at hand. The independent variables are manipulated to monitor the change it has on the dependent variable. It is often used in social sciences to observe human behavior by analyzing two groups affect of one group on the other.
3. Correlational Research Design:Correlational research is a non-experimental research design technique which helps researchers to establish a relationship between two closely connected variables. Two different groups are required to conduct this research design method. There is no assumption while evaluating a relationship between two different variables and statistical analysis techniques are used to calculate the relationship between them.

Correlation between two variables is concluded using a correlation coefficient, whose value ranges between -1 and +1. If the correlation coefficient is towards +1, it indicates a positive relationship between the variables and -1 indicates a negative relationship between the two variables. 

4. Diagnostic Research Design:In the diagnostic research design, a researcher is inclined towards evaluating the root cause of a specific topic. Elements that contribute towards a troublesome situation are evaluated in this research design method.

There are three parts of diagnostic research design:

• Inception of the issue
• Diagnosis of the issue
• Solution for the issue

5. Explanatory Research Design:In exploratory research design, the researcher’s ideas and thoughts are key as it is primarily dependent on their personal inclination about a particular topic. Explanation about unexplored aspects of a subject is provided along with details about what, how and why related to the research questions.

Elements of Research Design

A research design can be described as a conceptual structure within which research is going to be carried out. It comprises the blueprint for the collection, measurement and analysis of data. Decisions with regards to what, where, when, how much, by what means concerning an enquiry or a research design are taken.

A research design is the arrangement of conditions for collection and evaluation of data in a fashion which is designed to combine relevance to the research purpose with economy in process.

The key elements of a good research design are as under:

1. Research Design is a plan which identifies the sources and kinds of information strongly related to the research problem.
2. It is a strategy indicating which method is going to be employed for collecting and analyzing the data.
3. Additionally, it consists of the time and cost budgets because most research is done under these two constraints. In a nutshell a research design must contain:

• A clear statement of the research problem.
• Methods and techniques to be utilized for gathering information from the population to be researched.
• Approach to be utilized in processing and analyzing data.

Purpose of the Study

• Exploratory study: Carried out when not much is known about the problem at hand, or no details are available on how similar problems or research issues have been solved in the past.
• Descriptive study: Carried out as a way to determine and be able to describe the characteristics of the variables of interest in a situation characteristics of the variables of interest in a situation.
• Studies which engage in hypotheses testing generally explain the nature of certain relationships, or establish the differences among groups or the independence of two or more factors in a situation.

Type of Investigation

• Causality Research Design: A causal study is an inquiry to understand the cause of one or more problems.
• A correlational study: Is an inquiry to find out the key variables linked to the problem.

A causal study question:
Does cigarette smoking cause cancer?
A correlational study question:
Are cigarette smoking and cancer associated?
Or
Are cigarette smoking, consuming alcohol, and chewing tobacco related to cancer?
If so, which of these contributes most to the variance in the dependent variable?

Figure: Main Elements of Research Design

Researcher Interference

The extent of interference by the researcher with the normal flow of work at the workplace has a direct effect on whether the study performed is causal or correlational. A correlational study is carried out in the natural environment of the corporation with minimal interference by the researcher with the normal flow of work.

In studies carried out to determine cause-and-effect relationships, the investigator attempts to adjust specific variables in order to study the outcomes of such manipulation on the dependent variable of interest. Put simply, the researcher intentionally changes certain variables in the setting and disrupts the events as they normally happen in the business.

Study Setting

Correlational research is carried out in noncontrived settings (normal settings), as opposed to most causal studies are carried out in contrived settings.

Unit of Analysis

The unit of analysis means the degree of aggregation of the data gathered through the subsequent data analysis.

• Individual
• Dyads
• Groups
• Organizations
• Cultures

Time Horizon

Cross-Sectional Studies: A study can be carried out in which data are collected only once, perhaps during a period of days or weeks or months, to be able to answer a research question.

Longitudinal Studies: Researching people or phenomena at several point in time to be able to answer the research question. Due to the fact that data are collected at two different points in time, the study is not cross-sectional kind, but is carried longitudinally across a period of time. Longitudinal studies take a longer period and energy and cost a lot more than cross-sectional studies. Having said that, well-planned longitudinal studies can help you to recognize cause-and-effect relationships.

For example, you can study the product sales before and after an advertising campaign, and provided other environmental changes haven’t influenced on the results, you can attribute the increase in the sales volume, if any, to the advertisement.

A good research design must contain: a clear statement, Methods and techniques for data collection, processing and analyzing data.

Scientific research is a investigating and acquiring or expanding our understanding whereas nonscientific research is acquiring knowledge and truths about the world using techniques that do not follow the scientific method.

Scientific research is a logically stepped process used for investigating and acquiring or expanding our understanding. The findings of scientific research can be reproduced and demonstrated to be consistent. While in non scientific research, the research it’s not logically stepped process that used for investigating and acquiring or expanding our understanding

Scientific research acquiring knowledge and truths about the data or information using techniques that follow the scientific methods such as identification of a problem, formulation of statement of a problem, formulation of hypothesis, data analysis data recording, presentation and interpretation, testing hypothesis and recommendation and conclusion. while Non scientific acquiring knowledge and truths about the world using techniques without follow the scientific method.

Scientific research is a systematic way of gathering data and harnessing curiosity. This research provides scientific information and theories for the explanation of the nature and the properties of the world. It makes practical applications possible. While non scientific research does not follow systematic way of gathering data and harnessing curiosity

Scientific research is a systematic way of analyzing and interpreting new or existing material through experimentation and observation, While Non scientific research is based upon investigation of natural phenomenon without systematic

In general. Scientific research and non scientific research, both are used in collection of data, information and knowledge that can be added to the existing one. Can be used to solve different disputes such as political conflict economic issues and social conflict.

Basic Postulates of Scientific Method

The scientific method is, thus, based on certain basic postulates which can be stated as under:

(i) It relies on empirical evidence

(ii) It utilizes relevant concepts

(iii) It is committed to only objective considerations

(iv) It presupposes ethical neutrality, i.e., it aims at nothing but making only adequate and correct statements about population objects

(v) It results into probabilistic predictions

(vi) Its methodology is made known to all concerned for critical scrutiny are for use in testing the conclusions through replication

(vii) It aims at formulating most general axioms or what can be termed as scientific theories.

Thus, “the scientific method encourages a rigorous, impersonal mode of procedure dictated by the demands of logic and objective procedure.” Accordingly, scientific method implies an objective, logical and systematic method, i.e., a method free from personal bias or prejudice, a method to ascertain demonstrable qualities of a phenomenon capable of being verified, a method wherein the researcher is guided by the rules of logical reasoning, a method wherein the investigation proceeds inane orderly manner and a method that implies internal consistency.

Five (5) Major Characteristics of the Scientific Method

The scientific method is the system used by scientists to explore data, generate and test hypotheses, develop new theories and confirm or reject earlier results. Although the exact methods used in the different sciences vary (for example, physicists and psychologists work in very different ways), they share some fundamental attributes that may be called characteristics of the scientific method.

1. Empirical Observation

The scientific method is empirical. That is, it relies on direct observation of the world, and disdains hypotheses that run counter to observable fact. This contrasts with methods that rely on pure reason (including that proposed by Plato) and with methods that rely on emotional or other subjective factors.

2. Replicable Experiments

Scientific experiments are replicable. That is, if another person duplicates the experiment, he or she will get the same results. Scientists are supposed to publish enough of their method so that another person, with appropriate training, could replicate the results. This contrasts with methods that rely on experiences that are unique to a particular individual or a small group of individuals.

3. Provisional Results

Results obtained through the scientific method are provisional; they are (or ought to be) open to question and debate. If new data arise that contradict a theory, that theory must be modified. For example, the phlogiston theory of fire and combustion was rejected when evidence against it arose.

4. Objective Approach

The scientific method is objective. It relies on facts and on the world as it is, rather than on beliefs, wishes or desires. Scientists attempt (with varying degrees of success) to remove their biases when making observations.

5. Systematic Observation

Strictly speaking, the scientific method is systematic; that is, it relies on carefully planned studies rather than on random or haphazard observation. Nevertheless, science can begin from some random observation. Isaac Asimov said that the most exciting phrase to hear in science is not “Eureka!” but “That’s funny.” After the scientist notices something funny, he or she proceeds to investigate it systematically.

Types of Sampling

There are many different types of sampling methods, here’s a summary of the most common:

Cluster sampling

Units in the population can often be found in certain geographic groups or “clusters” for example, primary school children in Derbyshire.

A random sample of clusters is taken, then all units within the cluster are examined.

Advantages

• Quick and easy
• Doesn’t need complete population information
• Good for face-to-face surveys

Disadvantages

• Expensive if the clusters are large
• Greater risk of sampling error

Convenience sampling

Uses those who are willing to volunteer and easiest to involve in the study.

Advantages

• Subjects are readily available
• Large amounts of information can be gathered quickly

Disadvantages

• The sample is not representative of the entire population, so results can’t speak for them inferences are limited.
• Prone to volunteer bias

Judgement sampling

A deliberate choice of a sample the opposite of random

Advantages

• Good for providing illustrative examples or case studies

Disadvantages

• Very prone to bias
• Samples often small
• Cannot extrapolate from sample

Quota sampling

The aim is to obtain a sample that is “representative” of the overall population.

The population is divided (“stratified”) by the most important variables such as income, age and location. The required quota sample is then drawn from each stratum.

Advantages

• Quick and easy way of obtaining a sample

Disadvantages

• Not random, so some risk of bias
• Need to understand the population to be able to identify the basis of stratification

Simply random sampling

This makes sure that every member of the population has an equal chance of selection.

Advantages

• Simple to design and interpret
• Can calculate both estimate of the population and sampling error

Disadvantages

• Need a complete and accurate population listing
• May not be practical if the sample requires lots of small visits over the country

Systematic sampling

• After randomly selecting a starting point from the population between 1 and *n, every nth unit is selected.

*n equals the population size divided by the sample size.

Advantages

• Easier to extract the sample than via simple random
• Ensures sample is spread across the population

Disadvantages

• Can be costly and time consuming if the sample is not conveniently located

Importance of Sampling Design

Save Time

Contacting everyone in a population takes time. And, invariably, some people will not respond to the first effort at contacting them, meaning researchers have to invest more time for follow-up. Random sampling is much faster than surveying everyone in a population, and obtaining a non-random sample is almost always faster than random sampling. Thus, sampling saves researchers lots of time.

Save Money

The number of people a researcher contacts is directly related to the cost of a study. Sampling saves money by allowing researchers to gather the same answers from a sample that they would receive from the population.

Non-random sampling is significantly cheaper than random sampling, because it lowers the cost associated with finding people and collecting data from them. Because all research is conducted on a budget, saving money is important.

Collect Richer Data

Sometimes, the goal of research is to collect a little bit of data from a lot of people (e.g., an opinion poll). At other times, the goal is to collect a lot of information from just a few people (e.g., a user study or ethnographic interview). Either way, sampling allows researchers to ask participants more questions and to gather richer data than does contacting everyone in a population.

The Importance of Knowing Where to Sample

Efficient sampling has a number of benefits for researchers. But just as important as knowing how to sample is knowing where to sample. Some research participants are better suited for the purposes of a project than others. Finding participants that are fit for the purpose of a project is crucial, because it allows researchers to gather high-quality data.

For example, consider an online research project. A team of researchers who decides to conduct a study online has several different sources of participants to choose from. Some sources provide a random sample, and many more provide a non-random sample. When selecting a non-random sample, researchers have several options to consider. Some studies are especially well-suited to an online panel that offers access to millions of different participants worldwide. Other studies, meanwhile, are better suited to a crowdsourced site that generally has fewer participants overall but more flexibility for fostering participant engagement.

To make these options more tangible, let’s look at examples of when researchers might use different kinds of online samples.