Presentation of Data: Classification, frequency distribution, Discrete & continuous

17/04/2020 4 By indiafreenotes
  • It is the process of arranging data into homogeneous (similar) groups according to their common characteristics.
  • Raw data cannot be easily understood and it is not fit for further analysis and interpretation. This arrangement of data helps users in comparison and analysis.
  • For example, the Population of town can be grouped according to sex, age, marital status etc.

Classification of data

The method of arranging data into homogeneous classes according to some common features present in the data is called classification.

A planned data analysis system makes fundamental data easy to find and recover. This can be of particular interest for legal discovery, risk management and compliance. Written methods and set of guidelines for data classification should determine what levels and measures the company will use to organise data and define the roles of employees within the business regarding input stewardship. Once a data-classification scheme has been designed, security standards that stipulate proper approaching practices for each division and storage criteria that determine the data’s lifecycle demands should be discussed.

Objectives of Data Classification

The primary objectives of data classification are:

  • To consolidate the volume of data in such a way that similarities and differences can be quickly understood. Figures can consequently be ordered in a few sections holding common traits.
  • To aid comparison.
  • To point out the important characteristics of the data at a flash.
  • To give importance to the prominent data collected while separating the optional elements.
  • To allow a statistical method of the material gathered.
Definition of Classification Given by Prof. Secrist “Classification is the process of arranging data into sequences according to their common characteristics or Separating them into different related parts.”
(a) Meaning of Variable
  • The term variable is derived from the word ‘vary’ which means to differ or change. Hence, variable means the characteristic which varies or differs or changes from person to person, time to time, place to place etc. Or
  • A variable refers to quantity or attribute whose value varies from one investigation to another.
  • For example:

1.     “Price” is a variable as prices of different commodities are different.

2.     “Age” is a variable as age of different students varies.

3.     Some more examples are Height, Weight, Wages, Expenditure, Imports, Production, etc.

(B) Kinds of Variable:
(I) Discrete Variable
  • Variables which are capable of taking an only exact value and not any fractional value are termed as discrete variables.
  • For example, a number of workers or number of students in a class is a discrete variable as they cannot be in fraction. Similarly, a number of children in a family can be 1, 2 or so on, but cannot be 1.5, 2.75.
(II) Continuous Variable
  • Those variables which can take all the possible values (integral as well as fractional) in a given specified range are termed as continuous variables.
  • For example, Temperature, Height, Weight, Marks etc.

Methods of Classification

Following Are the Basis of Classification:
(1) Geographical Classification
  • When data are classified with reference to geographical locations such as countries, states, cities, districts, etc. it is known as Geographical Classification.
  • It is also known as ‘Spatial Classification’.
(2) Chronological Classification
  • When data are grouped according to time, such a classification is known as a Chronological Classification.
  • In such a classification, data are classified either in ascending or in descending order with reference to time such as years, quarters, months, weeks, etc.
  • It is also called ‘Temporal Classification’.
(3) Qualitative Classification
  • Under this classification, data are classified on the basis of some attributes or qualities like honesty, beauty, intelligence, literacy, marital status etc.
  • For example, Population can be divided on the basis of marital status as married or unmarried etc.
(4) Quantitative Classification
  • This type of classification is made on the basis some measurable characteristics like height, weight, age, income, marks of students, etc.