Consider making an inference about p1-p2, where there are x1successes inn1binomial trials and x2successes inn2binomial trials.

a. Describe the distributions of x1and x2.

b. Explain why the Central Limit Theorem is important in finding an approximate distribution forp^1-p^2

Short Answer

Expert verified

b. The central limit theorem approximates the distribution without considering the population's original distribution.

Step by step solution

01

Given information

We have, for the first trial

The number of binomial trials is n1and x1there are successes

For the second trial

There are binomial trials n2, and there arex2 successes.

02

Definition of binomial trials

When we have a prefixed number of trials to get the desired number of successes with a fixed probability of success throughout the experiment, the process will be well executed by binomial probabilities.

03

Importance of the central limit theorem

The central limit theorem helps to find the approximate distribution for the sample mean when the sample size is large enough (at least 30) regardless of the original distribution.

Hereand can be viewed as means of the number of successes per trial in the respective samples.

Hence the distribution of can be approximated using the central limit theorem, as it represents the difference in the sample mean for the number of successes per trial.

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Most popular questions from this chapter

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: 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)

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a. Specify the parameter of interest to the experimenters.

b. Set up the null and indispensable suppositions for testing whether the proportion of directors willing to offer windrowing services differs in Missouri and Illinois.

c. A Minitab analysis of the data is given below. Detect the test statistic on the printout.

d. provide the rejection region for the test using a = .01.

e. Detect the p- the value of the test on the printout.

f. Make the applicable conclusion using both the p-value and rejection region approach. Your conclusions should agree.

Redeeming tickets from textbook dispatches. Numerous companies now use textbook messaging on cell phones to sell their products. One way to do this is to shoot repairable reduction pasteboard (called an m- pasteboard) via a textbook. The redemption rate of m- tickets — the proportion of tickets redeemed — was the subject of a composition in the Journal of Marketing Research (October 2015). In a two-time study, over boardwalk shoppers shared by subscribing up to admit m-voucher. The experimenters were interested in comparing the redemption rates of m- tickets for different products in a sample of m- tickets for products vended at a milk-shake. Store, 79 were redeemed; in a sample of m- tickets for products vended at a donut store, 72 were redeemed.

a. Cipher the redemption rate for the sample of milk-shake m- tickets.

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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.
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