1. Why given analysis is statistically significant?
2. How each firm can be distinguished from each other statistically? Explain citing the relevant evidence from your Tukey HSD output above?
3. How does limiting the analysis to just this category change the results?
4. Please explain how you think Goodyear stands relative to its competitors with respect to run-on-flat tires:

Task 3: For this task, use the second JMP file I have provided, called Split TireDataJMP. The difference is that each of the 12 categories is now in its own column. This format for data is sometimes called "FAT" or "WIDE". It allows you to perform correlations and regression analysis. Use Fit Model to fit a linear regression model with Would Buy Again as the dependent variable and the other 11 survey questions as the independent variables. When you specify the model, Select "Minimal Report" (upper right hand side of screen). Reproduce your results here: Nominal Logistic Fit for Goodyear or Other Firm Effect Summary Source LogWorth WouldBuyAgain WetTraction 12349 Ride Quality Treadwear LightSnowTraction 1.703 Dry Traction 1.587 Hydroplaining Resistance 1.176 ComeringStability 0.497 DeepSnowTraction 0.480 Steering Response 0.480 Noise 0241 Ice Traction 0.145 Converged in Gradient 7 iterations Whole Model Test Model Loglikelihood DF ChiSquare Prob> Chisq Difference 160.33463 12 320.6693 ,0001" Full 331.50147 Reduced 491.03611 PValue 0.00000 0.00000 0.00028 0.01161 0.01983 0.02590 0.06675 0.31832 033106 0.34635 057419 0.71676 031 RSquare (U) 0.3260 AICC 689 265 BIC 757215 Observations for Sum Wats) 1404 Lack Of Fit Source DF Loglikelihood ChiSquare Lack Of Fit 1004 327.00992654,1799 Saturated 1016 441155 Prob>Chis Fitted 12 331.50147 1.0000 Parameter Estimates Term Estimate Std Error Chisquare Prob>Chisq Intercept -0.1176028 0.4320004 0.07 07855 ComeringStability 0.15434736 0.155093 0.99 0.3196 DeepSnowTraction 0.14252939 0.1470262 094 0.3323 Dry Traction 0.29732237 0.1327956 9.01 0.0252 Hydroplaining Resistance -0.2668751 0.1464799 3 32 0.0685 Ice Traction 0.05014112 0.13871 0.13 0.7177 LightSnow Traction -0.2752012 0.1 190027 5.35 0.02074 Noise 0.07377606 0.1317311 0.5754 RideQuality 0.43934867 0.1246523 1242 Steering Response 0.13995903 0.1491657 0.88 0.3404 Treadwear 0.2223626 0.0894132 0.0129 WetTraction -0.9427882 0.1401697 45.24 Chisq ComeringStability 1 0.99584137 0.3183 DeepSnow Traction 1 0.94476496 0.3311 Dry Traction 1 4.96293099 0.0259 Hydroplaining Resistance 1 3.36120686 0.0567 Ice Traction 1 0.13161964 0.7168 LightSnow Traction 1 5.42641804 0.0198 Noise 10.3157171 0.5742 RideQuality 1 13.175029 0.0003 Steering Response 1 0.88676606 0.3464 Treadwear 1 6.37022637 0.0116 WetTraction 1 52.4225717 0001 WouldBuyAgain 1 98.4740422 <.0001 given your interpretation of which variables are more or less statistically significant what would you advise any these tires companies to work on first in order improve their ratings be sure cite evidence from the analysis above. now fit same model but limit data just goodyear. reproduce results here: nominal logistic for goodyear other firm effect summary loqworth source wouleurgain wet traction ride quality hydroplaining resistance comerintability naise dupsnowtraction lichtsnowtraction stringspuns converged gradient iterations whole test loglikehood difference cnsquare probcns treathn rsquare observations sum wots lack de leylaethood cns quare probes chise fitted parameter estimates term sirtate std errow aime incept corneringstablicy deepsew drytraction ice ligh snowtraction noise rhquality singapore wellion wouldlyagain log odka s ter covariance intercept cornennstability deepshow drycoon hydroplaninghesistanceice racbon lightsnowtraction rideuality steering response treadwear wettraction wou duyan coming staty deepsnow dry ance icetraction doc lightsnow hisually wetractor d by again o. odos likelihood ratio tests comer ng stablity nparmdf chique pro cs rideusity uyigain explain how about tire should changes once try specifically: task this use second jmp file i have provided called split tiredatajmp. is that each categories its own column. format sometimes it allows perform correlations and regression analysis. a linear with buy as dependent variable survey questions independent variables. when specify select report right hand side screen logworth wouldbuyagain comeringstability deepsnowtraction loglikelihood df chisquare prob> Chisq Difference 160.33463 12 320.6693 ,0001" Full 331.50147 Reduced 491.03611 PValue 0.00000 0.00000 0.00028 0.01161 0.01983 0.02590 0.06675 0.31832 033106 0.34635 057419 0.71676 031 RSquare (U) 0.3260 AICC 689 265 BIC 757215 Observations for Sum Wats) 1404 Lack Of Fit Source DF Loglikelihood ChiSquare Lack Of Fit 1004 327.00992654,1799 Saturated 1016 441155 Prob>Chis Fitted 12 331.50147 1.0000 Parameter Estimates Term Estimate Std Error Chisquare Prob>Chisq Intercept -0.1176028 0.4320004 0.07 07855 ComeringStability 0.15434736 0.155093 0.99 0.3196 DeepSnowTraction 0.14252939 0.1470262 094 0.3323 Dry Traction 0.29732237 0.1327956 9.01 0.0252 Hydroplaining Resistance -0.2668751 0.1464799 3 32 0.0685 Ice Traction 0.05014112 0.13871 0.13 0.7177 LightSnow Traction -0.2752012 0.1 190027 5.35 0.02074 Noise 0.07377606 0.1317311 0.5754 RideQuality 0.43934867 0.1246523 1242 Steering Response 0.13995903 0.1491657 0.88 0.3404 Treadwear 0.2223626 0.0894132 0.0129 WetTraction -0.9427882 0.1401697 45.24 Chisq ComeringStability 1 0.99584137 0.3183 DeepSnow Traction 1 0.94476496 0.3311 Dry Traction 1 4.96293099 0.0259 Hydroplaining Resistance 1 3.36120686 0.0567 Ice Traction 1 0.13161964 0.7168 LightSnow Traction 1 5.42641804 0.0198 Noise 10.3157171 0.5742 RideQuality 1 13.175029 0.0003 Steering Response 1 0.88676606 0.3464 Treadwear 1 6.37022637 0.0116 WetTraction 1 52.4225717 0001 WouldBuyAgain 1 98.4740422 <.0001 given your interpretation of which variables are more or less statistically significant what would you advise any these tires companies to work on first in order improve their ratings be sure cite evidence from the analysis above. now fit same model but limit data just goodyear. reproduce results here: nominal logistic for goodyear other firm effect summary loqworth source wouleurgain wet traction ride quality hydroplaining resistance comerintability naise dupsnowtraction lichtsnowtraction stringspuns converged gradient iterations whole test loglikehood difference cnsquare probcns treathn rsquare observations sum wots lack de leylaethood cns quare probes chise fitted parameter estimates term sirtate std errow aime incept corneringstablicy deepsew drytraction ice ligh snowtraction noise rhquality singapore wellion wouldlyagain log odka s ter covariance intercept cornennstability deepshow drycoon hydroplaninghesistanceice racbon lightsnowtraction rideuality steering response treadwear wettraction wou duyan coming staty deepsnow dry ance icetraction doc lightsnow hisually wetractor d by again o. odos likelihood ratio tests comer ng stablity nparmdf chique pro cs rideusity uyigain explain how about tire should changes once try specifically>