In a bumper test, three test vehicles of each of three types of autos were crashed into a barrier at 5 mph, and the resulting damage was estimated. Crashes were from three angles: head-on, slanted, and rear-end. The results are shown below. Research questions: Is the mean repair cost affected by crash type andi'or vehicle type? Are the observed effects (if any} large enough to be of practical importance {as opposed to statistical significance)? 5 mph Collision Dal-rage (i) Crash Type Goliath Varmint Easel. Head0n 733 1,733 2,250 1,433 1, 553 1,6?0 853 1, 533 1,?40 Slant 1,433 1, 853 2,300 1,743 1,?33 1,510 1, 243 1, 553 2, 480 Rear-end T6!!! 856 1,650 1,253 1,553 1,650 978 1, 256 1,240 l 3 Click here for the Excel Data File [II-1) Choose the correct roweffect hypotheses. lb} Fill in the missing data. {Round your table of means values to 1 decimal place. SSand Fvalues to 2 decimal places, MS values to 3 decimal places, and p-values 1.0 4 decimal places.) Table of Mean: Factor 2 (Vehicle) Factor 1 (angle) Goliath Varmint Heasel Total Head0n Slant RearEnd Total TwoFactor ANOVA with Replication Source 55 of MS F p-value Factor 1 (Angle) Factor 2 (Vehicle) Interaction Error Total Id} Perform Tukey multiple comparison tests. {Input the mean values within the input boxes of the first row and input boxes of the first column. Round your t-values and critical values to 2 decimal places and other answers to 1 decimal place.) Post hoc analysis for Factor '1: TUkEy simultaneous calpar'ison tvalues (if. = 18) RearEnd Head0n Slant RearEnd Head0n Slant Critical values 'For experimentwise error rate: 8.35 8.31 Post hoc analysis for Factor 2: Post hoc analysis for Factor 2: Tukey simultaneous comparison t-values (d.f. = 18) Goliath Varmint Weasel Goliath Varmint Weasel critical values for experimentwise error rate: 0. 05 0.01