From the coefficient of multiple determination, we cannot detect the strength of the relationship between the dependent variable y and any individual independent variable.
A. True
B. False
You can detect the strength of the relationship between the variables.
true
The correct answer is B. False.
The coefficient of multiple determination, also known as R-squared (R^2), is a statistical measure that indicates the proportion of the variance in the dependent variable that can be explained by the independent variables in a regression model. It provides a measure of the strength of the relationship between the dependent variable (y) and all the independent variables together.
R-squared ranges from 0 to 1, with a value of 1 indicating a perfect fit of the model to the data. Therefore, a higher R-squared value suggests a stronger relationship between the dependent variable and the independent variables. On the other hand, a lower R-squared value indicates a weaker relationship.
While R-squared measures the overall strength of the relationship between the dependent variable and the independent variables in a multiple regression model, it does not provide information about the strength of the relationship between the dependent variable and each individual independent variable separately. To assess the strength of the relationship between the dependent variable and individual independent variables, other measures such as the coefficient of determination (R), t-tests, or p-values can be used in conjunction with R-squared.