Key Notes: Organisation of Data | Economics Class 11 - Commerce PDF Download

Organization of Data

Raw Data

Classification of Data

• Chronological Classification- They can be grouped according to time. 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.
• Spatial Classification- In Spatial Classification, the data are classified with reference to geographical locations such as countries, states, cities, districts, etc.
• Qualitative Classification- Sometimes you come across characteristics that cannot be expressed quantitatively. Such characteristics are called Qualities or Attributes. They cannot be measured. Yet these attributes can be classified on the basis of either the presence or the absence of a qualitative characteristic. Such a classification of data on attributes is called a Qualitative Classification.
• Quantitative Classification- Characteristics, like height, weight, age, income, marks of students, etc., are quantitative in nature. When the collected data of such characteristics are grouped into classes, it becomes a Quantitative Classification.

Types of Variables

• Continuous variable- A continuous variable can take any numerical values as fractional values, and values that are not exact fractions. Other examples of continuous variables are weight, time, distance, etc.
• Discrete variable- A discrete variable can take only certain values. Its value changes only by finite “jumps”. It “jumps” from one value to another but does not take any intermediate value between them. For example, a variable like the “number of students in a class”, for different classes, would assume values that are only whole numbers. It cannot take any fractional value like 0.5 because “half of a student” is absurd.

What is a frequency distribution?
A frequency distribution is a comprehensive way to classify raw data of a quantitative variable. It shows how different values of a variable are distributed in different classes along with their corresponding class frequencies. Frequency Curve is a graphic representation of a frequency distribution.

How to prepare Frequency Distribution?
While preparing a frequency distribution, the following five questions need to be addressed:

• Should we have equal or unequal-sized class intervals?- There are two situations in which unequal-sized intervals are used. First, when we have data on income and other similar variables where the range is very high.
• How many classes should we have?- The number of classes is usually between six and fifteen. In case, we are using equal-sized class intervals then a number of classes can be calculated by dividing the range (the difference between the largest and the smallest values of variable) by the size of the class intervals.
• What should be the size of each class?- The size of each class can be determined only after determining the classes.
• How should we determine the class limits?- Generally, open-ended classes such as “70 and over” or “less than 10” are not desirable. The lower and upper-class limits should be determined in such a manner that frequencies of each class tend to concentrate in the middle of the class intervals. Inclusive and exclusive class intervals.
• How should we get the frequency for each class?- Frequency of observation means how many times that observation occurs in the raw data.

Adjustment in class interval
The adjustment is done in the following way:

• Find the difference between the lower limit of the second class and the upper limit of the first class.
• Divide the difference obtained by two
• Subtract the value obtained from lower limits of all classes
• Add the value obtained to the upper limits of all classes.

Adjusted = (Adjusted Upper-Class Limit + Adjusted Lower-Class Limit)/2.
Methods of frequency calculation:

• Finding class frequency by tally marking
• Frequency distribution with unequal classes

Loss of information- While data is classified, a lot of information is lost in the process. This amount of data lost in the process of classification is called loss of information.
Frequency Array- The classification of data for a discrete variable is called frequency array. Since a discrete variable takes values and not intermediate fractional values between two integral values, we take frequencies that correspond to each of its integral values.

Bivariate Frequency Distribution

A Bivariate Frequency Distribution can be defined as the frequency distribution of two variables. Very often when we take a sample from a population we collect more than one type of information from each element of the sample, known as bivariate data. Such bivariate data can be summarised using a Bivariate Frequency Distribution.