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 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 table below.

		Position of Advertisement
Time of Day	On the Hour	On the Half-Hour	Early in Program	Late in Program
10:00 morning	43	37	62	50
	35	42	68	46
	40	39	66	50
4:00 afternoon	62	57	86	68
	60	64	81	60
	60	53	80	67
9:00 evening	105	95	127	103
	96	99	119	101
	102	102	128	109

ANOVA: Two-Factor With Replication
Summary	Hour	Half-Hour	Early	Late	Total
Morning
Count	3	3	3	3	12
Sum	118	118	196	146	578
Average	39.33	39.33	65.33	48.67	48.17
Variance	16.33	6.33	9.33	5.33	129.79
Afternoon
Count	3	3	3	3	12
Sum	182	174	247	195	798
Average	60.67	58.00	82.33	65.00	66.50
Variance	1.33	31.00	10.33	19.00	109.18
Evening
Count	3	3	3	3	12
Sum	303	296	374	313	1,286
Average	101.00	98.67	124.67	104.33	107.17
Variance	21.00	12.33	24.33	17.33	129.42
Total
Count	9	9	9	9
Sum	603	588	817	654
Average	67.00	65.33	90.78	72.67
Variance	745.25	702.75	711.19	624.50

ANOVA
Source of Variation	SS	df	MS	F	P-Value	F crit
Sample	21,883.56	2	10,941.78	754.61	.0000	3.403
Columns	3,666.33	3	1,222.11	84.28	.0000	3.009
Interaction	38.00	6	6.33	.44	.8469	2.508
Error	348.00	24	14.500
Total	25,935.89	35

(a)	Perform graphical analysis to check for interaction between time of day and position of advertisement. Then test for interaction with= .05.

F = .44,p-value = .8469,(Click to select)rejectdo not rejectH₀: there is(Click to select)nosomeinteraction

Graphical analysis(Click to select)supportsdoes not supportthe above conclusion.

(b)	Test the significance of time of day effects with= .05.

F = 754.61,p-value = less than.05;(Click to select)do not rejectrejectH₀: time of day is important

(c)	Test the significance of position of advertisement effects with= .05.

F = 84.28,p-value = less than.001;(Click to select)rejectdo not rejectH₀: position of the ads is important

(d)	Make pairwise comparisons of the morning, afternoon, and evening times by using Tukeysimultaneous 95 percent confidence intervals.(Round your answers to 2 decimal places. Negative amounts should be indicated by a minus sign.)

Tukey q.05	=3.53, MSE = 14.500
uMuA:	[,]
uMuE:	[,]
uAuE:	[,]

(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.)

u1u2:	[,]
u1u3:	[,]
u1u4:	[,]
u2u3:	[,]
u2u4:	[,]
u3u4:	[,]

(f)	Which time of day and advertisement position maximizes consumer response? Compute a 95 percent (individual) confidence interval for the mean number of calls placed for this time of day/ad position combination.(Round your answers to 2 decimal places.)

(Click to select)10:00 morning9:00 evening4:00 afternoon/(Click to select)late in the programearly in the programon the half-houron the hour

Confidence interval = [,]