As shown in your JMP outputs Attached the coefficients for Nose and HeadCirc might not be helpful to predict Height.

Conduct a hypothesis test to determine whether Nose and HeadCirc can be dropped from the model. i. (1 pt) State the null and alternative hypotheses. ii. (1 pt) State the full the reduced models. iii. Answer the following questions. a. (1 pt) Should we reject the null or fail to reject the null? b. (2 pts) Justify your decision in a. using a rejection region.

c. (1 pt) Justify your decision in a. using a p-value. (Put relevant JMP outputs in this blank) iv. (1 pt) Interpret your conclusion in the context

Response Height Whole Model LeftArm Nose HeadCirc LeftFoot Actual by Predicted Plot Leverage Plot Leverage Plot Leverage Plot Leverage Plot 30 80 80 BO 80 - 75 75 75 75 75 Height Leverage Residuals Height Leverage Residuals 70 Height Leverage Residual 70 Height Leverage Residuals Height Actual 70 70 70 65 65 65 65 65 60 60 30 60 T 26 28 30 5 54 56 58 60 32 22 24 26 28 30 32 65 70 75 80 22 24 LeftArm Leverage, P<.0001 nose leverage p="0.7659" headcirc leftfoot height predicted rmse="2.1834" rsq="0.77" pvalue="<.0001" effect summary source logworth leftarm .59260 residual by plot n of fit rsquare adj root mean square error response observations sum wgts analysis variance df squares f ratio model prob> F C. Total 54 1054.745 <.0001 parameter estimates term estimate std error t ratio prob>|t] Intercept 18.502649 7.830309 2.36 0.0221* LeftArm 0.8020485 0.170743 4.70 <.0001 nose headcirc leftfoot>