Regression Analysis: Days @ Gym in Febv Analysis of Variance Source DF Adj SS Ad

Question

Regression Analysis: Days @ Gym in Febv Analysis of Variance Source DF Adj SS Adi MS F-Value P-Value Regression 1 3.876 3876 022 0.645 Age Error Lack-of-Fit 22 462491 21.022 3.23 0.075 Pure Error 6 39.000 6.500 1 3.876 3.876 0.22 0.645 28 501.491 17.910 Total 29 505.367 Model Summary S R-sq R-sq(ad) R-sq(pred) 0.00% 4.23207 0.77% 0.00% Coefficients Coef SE Coef T-Value P-Value VIF Term Constant 14.17 241 5.88 0.000 Age 0.0245 0.0528 0.47 0.645 1.00 Regression Equation Days @ Gym in Feb = 14.17 + 0.0245 Age

Explanation / Answer

1. Slope = 0.0245 which is > 0 Therefore it is positive correlation between Age and Days Gym in Feb

If 1 year age increase then Days @Gym in Feb increase 0.0245

2. Intercept Y = 14.17
If the age is 0 then Days@Gym in Feb = 14.17
which is meaning less

3. R-Sq = 0.77% of variation in the variable Days Gym in Feb is explained by the variable Age

4. Lack of Fit

5. P-value of regression is 0.645 > alpha 0.05, so we accept H0
Thus we conclude that the regression equation is not best fit to the given datan

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