Co-efficient of non-determination:

The coefficient of non-determination, also known as the residual variance or the unexplained variance, is a measure used to determine the proportion of the dependent variable that is not explained by the independent variable(s). It is calculated by subtracting the coefficient of determination (R-squared) from 1.

Formula:
Coefficient of non-determination = 1 - R²

Given:
R = 0.6

Calculation:
Using the given value of R, we can calculate the coefficient of non-determination as follows:

Coefficient of non-determination = 1 - R²
= 1 - (0.6)²
= 1 - 0.36
= 0.64

Therefore, the coefficient of non-determination is 0.64.

Explanation:

The coefficient of determination (R-squared) is a statistical measure that represents the proportion of the dependent variable's variance that can be explained by the independent variable(s) in a regression model. It ranges from 0 to 1, where 0 indicates no relationship between the variables and 1 indicates a perfect relationship.

The coefficient of non-determination, on the other hand, represents the proportion of the dependent variable's variance that cannot be explained by the independent variable(s). It is calculated by subtracting the coefficient of determination from 1.

In this case, the given coefficient of determination (R) is 0.6. To calculate the coefficient of non-determination, we subtract the square of R (0.6² = 0.36) from 1. This gives us a value of 0.64, which represents the proportion of the dependent variable's variance that is not explained by the independent variable(s).

In summary, the coefficient of non-determination provides insight into the amount of unexplained variation in the dependent variable and is useful for evaluating the goodness of fit of a regression model.