Correlation: Meaning, Definition and Types

Correlation?

Correlation indicates the relationship between two or more variables of a series so that changes in the values of one variable are associated with changes in the value of other variables. 

Definitions of Correlation

According to L.R. Conner- “If two or more quantities vary in sympathy so that movements in one tend to. accompanied by corresponding movements in the other(s) then they tend are said to be. correlated”

According to Croxton and Cowden- “Correlation is defined as “When the relationship is of a quantitative nature, the appropriate statistical tool for discovering and measuring the relationship and expressing it in a brief formula is known as correlation.”

According to W.I.King “Correlation means that between two series or groups of data there exists some casual connection.”

Correlation studies the relationship between two variables in which change in the value of one variable causes change in the other variable.

Types of Correlation

Correlation can be classified on the basis of three Categories.

On the basis of Direction of Change

1. Positive Correlation
2. Negative Correlation

On the Basis of Ratio of Variations in the variables

1. Linear Correlation
2. Non-Linear Correlation

On the Basis of the number of variables
1. Simple Correlation
2. Multiple Correlation
3. Partial Correlation

On the basis of Direction of Change

1. Positive Correlation: The Correlation is regarded as positive when the two variables move in the same direction. It means an increase in the value of one variable leads to an increase in the value of another variable. Similarly, a decrease in the value of variable results to a decrease in the value of another variable. For example, an increase in the price of a commodity also increases the supply of that commodity and decrease in the price of a commodity also decreases the supply of that commodity. When both variables move in the same direction. 

2. Negative Correlation: When the value of two quantities moves in the opposite direction the correlation is said to be negative. It means if the value of one variable increases, the value of another variable will decrease. For example, if the price of a commodity increases, the demand of that commodity decreases due to decrease in the amount of purchase, people’s Age, and playing Habbits. Negative correlation is also called inverse correlation. Two variables move in the opposite direction.

On the Basis of Ratio of Variations in the variables

1. Linear Correlation: When the ratio of change in two variables is constant, the correlation is said to be linear. For example, if with a 5% increase in the price of a commodity, the sales are reduced by 10%, There is a linear relationship between price and sales. When two variables change in a constant proportion. 

2. Non-Linear Correlation: When the ratio of change in two variables is not constant, the correlation is said to be non-linear. For example, with an increase of 10% in the price of an article, the sale is reduced by 5% in one area and by 8% in another area. There is non-linear relationship between two variables. When two variables do not change in the same proportion.

On the basis of the number of variables

1. Simple Correlation: When the change in one variable affects only one other variable, means, only two variables are affected, then it is said to be simple correlation. Example: Price and Demand, Income and Expense etc. The relationship between two variables are studied. 

2. Multiple Correlation: When more than one variable is affected, it is said to be a multiple correlation. For Example: More Rainfall increases agriculture as well as the amount of fertilizers used by a farmer. The relationship between three or more than three variables are studied.

3. Partial Correlation: In such correlation, only correlation between two variables is measured while more than two variables are involved. For Example, if we calculate crop yield of agriculture depending on the amount of fertilizer used ignoring the amount of rainfall.

Degree of Correlation

The degree of intensity of relationship between two variables is measured with the coefficient of correlation.

The degree of correlation can be as follows:

1. Perfect Correlation: A correlation in which a relationship between two variables that moves in one direction and in the same proportion, correlation between them is perfect. It can be either positive(+1) or negative(-1).
2. Absence of Correlation: If there is no relationship between the two variables, then there is no correlation between them. It means there is absence of Correlation.
3. Limited Degree of Correlation: When the values of Coefficient of correlation lies between +1 and -1 except zero.

It can be High, Low and Moderate:

High: Coefficient of correlation lies between ±0.75 and ±1.

Moderate: Coefficient of correlation lies between ± 0.25 and ±75.

Low: Coefficient of correlation lies between 0 and ±0.25.

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