Save Answer When designing political advertising, like any advertising, it is important to capture the attention of the people watching the advertisements. A political party designs 4 ads for the an upcoming election based loosely around strategies that could be described as benfit campaign, mixed campagin, scare campaign and vision campaign. They then recuit some volunteers who randomly watch 1 of the ads wearing a special headset, which by tracking eye movement, can measure how much time the person is actually watching the screen during the 30 second ad. The client is interested in which type of ad has people looking at the screen the most and ideally one which keep the viewers gaze for at least 20 seconds on average. A statistician was asked to analyse the data using ANOVA methodology, some of which is presented below. Unfortunately she was not able to complete the analysis and you have been asked to answer the questions below, which primarily concern finding the type of ad with the highest time of viewer actually looking at the screen. > AnovaModel. 1 summary(AnovaModel. 1) Df Sum Sq Mean Sq F value Pr(>F) type 3 786.3 262.1 31.57 1.4e-12 *** Residuals 63 523.1 8.3 Signif. codes: 0 '*** 0.001 "** 0.01 '* 0.05 .' 0.1 "' 1 > with(adds2, numSummary(time, groups=type, statistics=c("mean", "sd"))) mean sd data:n Benefit 14.94790 2.615640 16 Mixed 18.09307 2.455451 16 Scare 20.52128 3.470403 18 Vision 11.54129 2.798228 17 Multiple Comparisons of Means: Tukey Contrasts Fit: aov(formula = time ~ type, data = adds2) Linear Hypotheses:Multiple Comparisons of Means: Tukey Contrasts Fit: aov(formula = time ~ type, data = adds2) Linear Hypotheses: Estimate Std. Error t value Pr(>|t)) Mixed - Benefit == 0 3.1452 1.0188 3.087 0.01527* Scare - Benefit == 0 5.5734 0.9901 5.629 levene Test(time ~ type, data=adds2, center="median") Levene's Test for Homogeneity of Variance (center = "median") Df F value Pr(>F) group 3 1.3788 0.2574 6363 Unless otherwise indicated all questions in this test are talking about the ANOVA output above. Define relevant mean parameters and state the appropriate null and alternative hypotheses to be tested here. For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). BIUS Paragraph V Arial V 10pt V V V A V V IX . . . E E E X2 X2 - ABC V V X EXE T ({} O