I AM NOT SUBMITTING MULTIPLE QUESTIONS. THIS IS ONE ENTIRE QUESTION WITH MULTIPLE PARTS IN IT. THE GUIDELINES ALLOW ME TO SUBMIT ONE QUESTION PER POST WITH MULTIPLE PARTS. THE 1ST WINDOW OF THE QUESTION IS DATA AND THE 2ND WINDOW INCLUDES ALL THE QUESTIONS FROM B - F.

There is NO 5A

For 5B & C) The answer is either "reject" or "do not reject"

For 5F) The answer for FIRST blank is either "10:00 morning", "4:00 afternoon", or "9:00 evening". The answer for SECOND blank is either "early in the program", "late in the program", "on the half-hour", or "on the hour"

Chapter 12 End of Chapter Assignment Saved Help (b) Test the significance of time of day effects with a - .05. 5 F = 913.71. p value less than 05 F = HO: time of day is important 5 points Skipped 1 points 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. The Telemarketing Data and the Excel Output of a two-way ANOVA Position of Advertisement Time of Day On the Hour on the Balt-Hour Early in Program Late in Program 10:00 morning 35 62 43 65 35 4:00 afternoon SB 87 61 61 59 54 9:00 evening 105 98 126 104 123 101 104 103 125 110 Skipped - Book 45 37 41 52 51 47 47 58 . (c) Test the significance of position of advertisement effects with a-.05. Book F = 96.58, p value = less than .001; HO: position of the ads is important References Hint Late Total References werage 145 43.33 12 575 47.92 121.54 ANOVA: Two-Factor With Replication Summary Hour Halt-Hour Early Morning Count Sun 123 193 41.00 54.33 Variance 16.00 19.00 4.33 Afternoon Count 3 3 Sun 182 173 249 Average 57.67 83.00 Variance 2.33 12.33 12.00 Evening Count Sun 304 300 374 Average 101.33 100.00 124.67 Variance 30.33 7.00 2.33 Total Count 9 9 9 Sun 509 587 816 Average 67.57 65.22 90.67 Variance 722.25 762.44 720.25 192 54.00 15.00 12 796 65.34 114.24 (d) Make pairwise comparisons of the morning, afternoon, and evening times by using Tukey simultaneous 95 percent confidence intervals. (Round your answers to 2 decimal places. Negative amounts should be indicated by a minus sign.) 3 315 105.00 21.00 12 1,293 107.75 118.75 Tuky 0,05 = 3.53, MSE = 12.333 M-WA UM-E A-VE 552 72.44 652.78 le) 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.) ANOVA Source of Variation Sample Columns Interaction Error Total dr 2 3 MS 11,269.00 1,192.07 SS 22,538.17 3,575.22 27.61 295.00 26, 438.00 913.71 96.65 .37 P-Value F crit 3.403 .0000 .8888 2.508 ut-2 -2 1-3 24 12.333 35 2-3 | 42 - 44 3-4 1 1 1 (f) Which time of day and advertisement position maximizes consumer response? Computea 95 percent individual) confidence interval for the mean number of calls placed for this time of daylad position combination (Round your answers to 2 decimal places.) Hall Ey La Confidence interval (b) Test the significance of time of day effects with a = .05. Chapter 12 End of Chapter Assignment Saved Help (b) Test the significance of time of day effects with a - .05. 5 F = 913.71. p value less than 05 F = HO: time of day is important 5 points Skipped 1 points 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. The Telemarketing Data and the Excel Output of a two-way ANOVA Position of Advertisement Time of Day On the Hour on the Balt-Hour Early in Program Late in Program 10:00 morning 35 62 43 65 35 4:00 afternoon SB 87 61 61 59 54 9:00 evening 105 98 126 104 123 101 104 103 125 110 Skipped - Book 45 37 41 52 51 47 47 58 . (c) Test the significance of position of advertisement effects with a-.05. Book F = 96.58, p value = less than .001; HO: position of the ads is important References Hint Late Total References werage 145 43.33 12 575 47.92 121.54 ANOVA: Two-Factor With Replication Summary Hour Halt-Hour Early Morning Count Sun 123 193 41.00 54.33 Variance 16.00 19.00 4.33 Afternoon Count 3 3 Sun 182 173 249 Average 57.67 83.00 Variance 2.33 12.33 12.00 Evening Count Sun 304 300 374 Average 101.33 100.00 124.67 Variance 30.33 7.00 2.33 Total Count 9 9 9 Sun 509 587 816 Average 67.57 65.22 90.67 Variance 722.25 762.44 720.25 192 54.00 15.00 12 796 65.34 114.24 (d) Make pairwise comparisons of the morning, afternoon, and evening times by using Tukey simultaneous 95 percent confidence intervals. (Round your answers to 2 decimal places. Negative amounts should be indicated by a minus sign.) 3 315 105.00 21.00 12 1,293 107.75 118.75 Tuky 0,05 = 3.53, MSE = 12.333 M-WA UM-E A-VE 552 72.44 652.78 le) 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.) ANOVA Source of Variation Sample Columns Interaction Error Total dr 2 3 MS 11,269.00 1,192.07 SS 22,538.17 3,575.22 27.61 295.00 26, 438.00 913.71 96.65 .37 P-Value F crit 3.403 .0000 .8888 2.508 ut-2 -2 1-3 24 12.333 35 2-3 | 42 - 44 3-4 1 1 1 (f) Which time of day and advertisement position maximizes consumer response? Computea 95 percent individual) confidence interval for the mean number of calls placed for this time of daylad position combination (Round your answers to 2 decimal places.) Hall Ey La Confidence interval (b) Test the significance of time of day effects with a = .05