A telemarketing firm has studied the effects of two factors on the response to its television advertisements. The first factor is the time of day at which the ad is run, while the second is the position of the ad within the hour. The data in the following table, which were obtained by using a completely randomized experimental design, give the number of calls placed to an 800 number following a sample broadcast of the advertisement. If we use Excel to analyze these data, we obtain the output in the table below. \begin{tabular}{lrrrrrr} ANOVA & & & & & \\ Source of Variation & \multicolumn{1}{c}{ SS } & df & \multicolumn{1}{c}{ MS } & F & P-Value & F crit \\ Sample & 22,616.22 & 2 & 11,308.11 & 1,017.73 & .0000 & 3.403 \\ Columns & 3,746.31 & 3 & 1,248.77 & 112.39 & .0000 & 3.009 \\ Interaction & 27.78 & 6 & 4.63 & .42 & .8606 & 2.508 \\ Error & 266.67 & 24 & 11.111 & & \\ Total & 26.656 .97 & 35 & & & \end{tabular} (e) Make pairwise comparisons of the four ad positions by using Tukey simultaneous 95 percent confidence intervals. (Round your answers to 2 decimal places. Negative amounts should be indicated by a minus sign.)