In the ANOVA table for a multiple regression, which of the following is not true? a. The mean square due to the regression, MSR, divided by the mean square error, MSE, equals the F ratio used for testing the significance of the regression as a whole. b. A small F ratio leads to a small p-value, indicating that the regression has at least some explanatory power. c. The sum of squares due to the regression, SSR, and the sum of squares due to errors, SSE, sum to SST, which equals the sum of squared deviations of Y values from the mean of Y. d. The degrees of freedom for the explained variation and the degrees of freedom for the unexplained variation sum to n-1, where n is the sample size.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
In the ANOVA table for a multiple regression, which of the following is not true?
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