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?