The value of the sum of squares for regression, SSR, can never be smaller than 0.0.Group of answer choicesTrueFalse

What would be the value of the sum of squares due to regression (SSR) if the total sum of squares (SST) is 25.32 and the sum of squares due to error (SSE) is 6.89?

What would be the coefficient of determination if the total sum of squares (SST) is 23.29 and the sum of squares due to regression (SSR) is 10.03?

If the standard error of estimate  = 20 and n = 8, then the sum of squares for error, SSE, is 2400.Group of answer choicesTrueFalse

The least squares regression line minimizes the sum of the _____Group of answer choicessquared differences between actual and predicted y valuesabsolute deviations between actual and predicted x valuesdifferences between actual and predicted y valuesabsolute deviations between actual and predicted y values

the problem with infinite regression is that it does not explain anything. Group of answer choicesTrueFalse