Properties of Coefficient of Correlation

1. Coefficient of Correlation is Independent of change of origin and scale of measurements: Coefficient of Correlation is not affected by the change of origin and scale of measurement.

2. Coefficient of Correlation lies between -1 and +1:  The property of r also serves as a useful check on the correctness of the calculations. If the value of r lies outside the range, then it would mean that there is some error in the calculations.

3. Zero Correlation: If two variables (say X and Y) are independent of each other, in that case, the coefficient of correlation between them will be zero.

4. Measure of Linear Relationship: The coefficient of correlation is a measure that helps in determining the linear relationship between two variables. If both the variables (say X and Y) increase or decrease together, then r will be positive. However, if one variable increases when the other variable decreases or vice-versa, then r will be negative.

Karl Pearson’s Coefficient of Correlation | Assumptions, Merits and Demerits

Similar Reads

What is Karl Pearson’s Coefficient of Correlation?

The first person to give a mathematical formula for the measurement of the degree of relationship between two variables in 1890 was Karl Pearson. Karl Pearson’s Coefficient of Correlation is also known as Product Moment Correlation or Simple Correlation Coefficient. This method of measuring the coefficient of correlation is the most popular and is widely used. It is denoted by ‘r’, where r is a pure number which means that r has no unit....

Karl Pearson’s Coefficient of Correlation and Covariance

Karl Pearson’s method of determining coefficient of correlation is based on the covariance of the given variables. Covariance is a statistical representation of the degree to which the two given variables vary together. Basically, Covariance is a number reflecting the degree to which the two variables vary together. The symbol of Covariance of two variables (say X and Y) is denoted by COV(X, Y)....

Examples of Karl Pearson’s Coefficient of Correlation

Example 1:Determine the Coefficient of Correlation between X and Y. The summation of the product of deviations of Series X and Y from their respective means is 200. Solution:The figures given are: N = 30, σx = 4, σy = 3, and ∑xy = 200 [Tex]r=\frac{\sum{xy}}{N\times{\sigma_x}\times{\sigma_y}} [/Tex] [Tex]=\frac{200}{30\times4\times3}=\frac{50}{90}=0.5 [/Tex] Coefficient of Correlation = 0.5 It means that there is a positive correlation between X and Y....

Features of Karl Pearson’s Coefficient of Correlation

The main features of Karl Pearson’s Coefficient of Correlation are as follows:...

Assumptions of Coefficient of Correlation

The assumptions on which Karl Pearson’s Coefficient of Correlation is based are as follows:...

Properties of Coefficient of Correlation

1. Coefficient of Correlation is Independent of change of origin and scale of measurements: Coefficient of Correlation is not affected by the change of origin and scale of measurement....

Merits of Karl Pearson’s Coefficient of Correlation

Various advantages of Karl Pearson’s Coefficient of Correlation are as follows:...

Demerits of Karl Pearson’s Coefficient of Correlation

Various disadvantages of Karl Pearson’s Coefficient of Correlation are as follows:...

Karl Pearson’s Coefficient of Correlation – FAQs

What is Karl Pearson’s Coefficient of Correlation?...