These notes for CBSE Class 11 Economics, Chapter 7, focus on Correlation. Correlation is defined as the study of the relationship between two variables where a change in one causes a change in the other, denoted by 'r'. The chapter details various kinds of correlation: positive and negative, linear and non-linear, and simple versus multiple. It explains positive correlation (variables move in the same direction) and negative correlation (variables move in opposite directions). Linear correlation involves changes in a constant proportion, while non-linear does not. Simple correlation studies two variables, and multiple correlation studies three or more. Degrees of correlation range from perfect positive (+1) and perfect negative (-1) to absence of correlation (0) and limited degrees (high, moderate, low) based on the 'r' value. Key methods for finding correlation are Karl Pearson's coefficient, Spearman's Rank Correlation, and the Scatter Diagram. The notes also briefly touch upon the merits and demerits of Karl Pearson's and Spearman's methods, and the scatter diagram. These notes are valuable for understanding the core concepts and preparing for exams.
Last optimized 10 Aug 2026
Correlation studies the relationship between tow variables in which change in the value of one variable causes change in the other variable. It is denoted by letter ‘r’.
1. Positive and Negative correlation.
2. Linear and non – linear correlation.
3. Simple and multiple correlations.
Positive correlation: When both variables move in the same direction. If one increases, other also increases and vice-versa.
Negative correlation: - When two variables move in the opposite direction, they are negatively correlated.
Linear Correlation: When two variables change in a constant proportion.
Non- linear correlation: When two variables do not change in the same proportion.
Simple correlation : Relationship between two variables are studied.
Multiple Correction : Relationship between three or more than three variables are studied.
1. Perfect Correlation: When values of both variables changes at a constant rate
Types
Perfect positive correlation : when values of both variables changes at a constant ratio in the same direction correlation coefficient value (r) is + 1
Perfect negative correlation : When values of both the variables change at a constant ratio in opposite direction. Value of coefficient of correlation is -1
2. Absence of correlation : When there is no relation between the variables r = 0
3. Limited degree correlation : The value of r varies between more than O and less than 1
Types - a) High : r his between ± 0.7 & 0.999
b) Moderate = r lies between ± 0.5 and + 0.699
c) Low: r < ± 0.5
a) Karl Pearson’s coefficient method b) Rank method / Spearman’s coefficient method c) Scatter Diagram
Where X = X – X, Y = Y – Y
N = number of observations OR
Assumed Mean Method
1. Helps to find direction of correlation 2. Most widely used method
1. Based on large number of assumptions 2. Affected by extreme values (B) Spearmans’s Rank Correlation Method
rs = Spearman’s rank correlation
•D2 = Sum of squares of difference of ranks
N = Number of observation
M = number of items with repeated ranks.
1. Simple and easy to calculate 2. Not affected by extreme values
1. Not Suitable for grouped data
2. Not based on original values of observations.
(C) Scatter Diagram – Given data are plotted on a graph paper. By looking at the scatter of points on the graph, degree and direction of two variables can be found.
1. Most simplest method. 2. Not affected by size of extreme values.
1. Exact degree of correlation cannot be found.
1 Mark questions
1. Give the meaning of correlation.
2. What is absence of correlation?
3. What is scatter diagram?
4. What does it mean if the correlation between two variables is + 1?
5. What is positive correlation?
4 Mark questions
1. Calculate Karl Pearson’s coefficient of correlation from the following:-
Correlation studies the relationship between two variables where a change in one variable causes a change in the other. It is denoted by the letter 'r'.
The main kinds of correlation are positive and negative, linear and non-linear, and simple and multiple correlations.
Positive correlation occurs when two variables move in the same direction; if one increases, the other also increases, and vice-versa.
A correlation coefficient of +1 signifies perfect positive correlation, meaning the values of both variables change at a constant ratio in the same direction.
Absence of correlation means there is no relation between the variables, and the correlation coefficient (r) is 0.
The different methods are Karl Pearson's coefficient method, Rank method (Spearman's coefficient method), and Scatter Diagram.
A scatter diagram is a method where data points are plotted on a graph paper to visually determine the degree and direction of correlation between two variables.
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