Question: Consumers’ attitudes toward advertising. The two most common marketing tools used for product advertising are ads on television and ads in a print magazine. Consumers’ attitudes toward television and magazine advertising were investigated in the Journal of Advertising (Vol. 42, 2013). In one experiment, each in a sample of 159 college students were asked to rate both the television and the magazine marketing tool on a scale of 1 to 7 points according to whether the tool was a good example of advertising, a typical form of advertising, and a representative form of advertising. Summary statistics for these “typicality” scores are provided in the following table. One objective is to compare the mean ratings of TV and magazine advertisements.

a. The researchers analysed the data using a paired samples t-test. Explain why this is the most valid method of analysis. Give the null and alternative hypotheses for the test.

b. The researchers reported a paired t-value of 6.96 with an associated p-value of .001 and stated that the “mean difference between television and magazine advertising was statistically significant.” Explain what this means in the context of the hypothesis test.

c. To assess whether the result is “practically significant,” we require a confidence interval for the mean difference. Although this interval was not reported in the article, you can compute it using the information provided in the table. Find a 95% confidence interval for the mean difference and interpret the result. What is your opinion regarding whether the two means are “practically significant.”

Source: H. S. Jin and R. J. Lutz, “The Typicality and Accessibility of Consumer Attitudes Toward Television Advertising: Implications for the Measurement of Attitudes Toward Advertising in General,” Journal of Advertising, Vol. 42, No. 4, 2013 (from Table 1)

Short Answer

Expert verified

a.

b. The null hypothesis is rejected.

c. The 95% confidence interval for the mean difference is (0.322 to 0.578).

Step by step solution

01

(a) Null and alternative hypothesis of the test

The researchers examined parred information since two separate evaluations were acquired from each student, i.e., each student supplied two ratings. As a result, a television mating commercial, as well as magazine scores, are linked as well as reliant.

02

(b) Context of a hypothesis test

The p-value < 0.001 of the discovery is significant. The null hypothesis is rejected. We may infer that the average difference in advertising among magazines and television was statistically significant.

03

(c) Practically significant

Let 105 be

with

The 95% confidence interval for the mean difference is (0.322 to 0.578). We may infer that the two means are statistically significant because the confidence intervals do not include 0.

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Most popular questions from this chapter

Question: Impact of race on football card values. Refer to the Electronic Journal of Sociology (2007) study of the Impact of race on the value of professional football players’ “rookie” cards, Exercise 12.72 (p. 756). Recall that the sample consisted of 148 rookie cards of NFL players who were inducted into the Football Hall of Fame (HOF). The researchers modelled the natural logarithm of card price (y) as a function of the following independent variables:

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  1. The model E(y)=β0+β1x1+β2x2+β3x3+β4x4+β5x5+β6x6+β7x7+β8x8+β9x9+β10x10+β11x11+β12x12 was fit to the data with the following results:R2=0.705,Ra2=0.681,F=26.9.Interpret the results, practically. Make an inference about the overall adequacy of the model.
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  4. Write a first-order model for E(y) as a function of card vintage x3and position x5-x12that allows for the relationship between price and vintage to vary depending on position.

4.134 Refer to Exercise 4.133. Find the following probabilities:

a.P(20x30)b.P(20<x30)c.P(x30)d.P(x45)e.(x40)f.(x<40)g.P(15x35)h.P(21.5x31.5)

Question: Promotion of supermarket vegetables. A supermarket chain is interested in exploring the relationship between the sales of its store-brand canned vegetables (y), the amount spent on promotion of the vegetables in local newspapers(x1) , and the amount of shelf space allocated to the brand (x2 ) . One of the chain’s supermarkets was randomly selected, and over a 20-week period, x1 and x2 were varied, as reported in the table.

Week

Sales, y

Advertising expenses,

Shelf space,

Interaction term,

1

2010

201

75

15075

2

1850

205

50

10250

3

2400

355

75

26625

4

1575

208

30

6240

5

3550

590

75

44250

6

2015

397

50

19850

7

3908

820

75

61500

8

1870

400

30

12000

9

4877

997

75

74775

10

2190

515

30

15450

11

5005

996

75

74700

12

2500

625

50

31250

13

3005

860

50

43000

14

3480

1012

50

50600

15

5500

1135

75

85125

16

1995

635

30

19050

17

2390

837

30

25110

18

4390

1200

50

60000

19

2785

990

30

29700

20

2989

1205

30

36150

  1. Fit the following model to the data:yβ0+β1x1+β2x2+β3x1x2+ε
  2. Conduct an F-test to investigate the overall usefulness of this model. Useα=.05 .
  3. Test for the presence of interaction between advertising expenditures and shelf space. Useα=.05 .
  4. Explain what it means to say that advertising expenditures and shelf space interact.
  5. Explain how you could be misled by using a first-order model instead of an interaction model to explain how advertising expenditures and shelf space influence sales.
  6. Based on the type of data collected, comment on the assumption of independent errors.

Question: Find the following probabilities for the standard normal random variable z:

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Gonzaga University professors conducted a study of television commercials and published their results in the Journal of Sociology, Social Work and Social Welfare (Vol. 2, 2008). The key research question was as follows: “Do television advertisers use religious symbolism to sell goods and services?” In a sample of 797 TV commercials collected ten years earlier, only 16 commercials used religious symbolism. Of the sample of 1,499 TV commercials examined in the more recent study, 51 commercials used religious symbolism. Conduct an analysis to determine if the percentage of TV commercials that use religious symbolism has changed over time. If you detect a change, estimate the magnitude of the difference and attach a measure of reliability to the estimate.

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