We give JMP output of regression analysis. Above output we givethe regression model and the number of observations, n,used to perform the regression analysis under consideration. Usingthe model, sample size n, and output:
Model: y = β0 +β1x1 +β2x2 +β3x3 +ε       Sample size:n = 30
| Summary of Fit |
| RSquare | 0.987331 |
| RSquare Adj | 0.985869 |
| Root Mean Square Error | 0.240749 |
| Mean of Response | 8.382667 |
| Observations (or Sum Wgts) | 30 |
|
| Analysis of Variance |
| Source | df | Sum of
Squares | Mean
Square | F Ratio |
| Model | 3 | 117.438830 | 39.14630 | 675.4012 |
| Error | 26 | 1.506960 | 0.05800 | Prob > F |
| C. Total | 29 | 118.945790 | | <.0001* |
(1) Report the total variation, unexplainedvariation, and explained variation as shown on the output.(Round your answers to 4 decimal places.) (2) Report R2 andR¯¯¯2R¯2 as shown on the output. (Round youranswers to 4 decimal places.) (3) Report SSE,s2, and s as shown on the output.(Round your answers to 4 decimal places.) (4) Calculate the F(model) statisticby using the explained variation, the unexplained variation, andother relevant quantities. (Round your answer to 2 decimalplaces.) (5)  Use the F(model)statistic and the appropriate critical value to test thesignificance of the linear regression model under consideration bysetting α equal to .05. (6) Find the p−value related toF(model) on the output. Using the p−value, testthe significance of the linear regression model by setting α = .10,.05, .01, and .001. What do you conclude? |
