QUESTION 7 If, after the ANOVA, we were calculating a confidence interval for the mean watching time of benefit, what would the relevant standard deviation be for the calculation? (Please give your answer to 1 decimal place) QUESTION 8 If, after the ANOVA, we were calculating a confidence interval for the mean difference between the watching time of mixed and values, what would the relevant degrees of freedom be for the t-critical value we use?QUESTION 1 3 points Saved 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 values 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 3 667.1 222.36 33.98 4.9e-14 *** Residuals 76 497.3 6.54 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 14.73989 1.578403 21 Mixed 12.84708 3.043579 18 Scare 20.38194 2.588692 17 Values 18.62305 2.819337 24 Multiple Comparisons of Means: Tukey Contrasts Fit: aov(formula = time ~ type, data = adds2) Linear Hypotheses: Estimate Std. Error t value Pr(>It)) Mixed - Benefit = = 0 -1.8928 0.8217 2.304 0. 106 Scare - Benefit == 0 5.6420 0.8346 6.760 levene Test(time - type, data=adds2, center="median") Levene's Test for Homogeneity of Variance (center = "median") Df F value Pr(>F) group 3 1.9816 0.1238 76 Unless otherwise indicated all questions in this test are talking about the ANOVA output above