The data for a random sample of 10 paired observations is shown below.

PairSample from Population 1

(Observation 1)

Sample from Population 2 (Observation 2)
12345678910
19253152493459471751
24273653553466512055

a. If you wish to test whether these data are sufficient to indicate that the mean for population 2 is larger than that for population 1, what are the appropriate null and alternative hypotheses? Define any symbols you use.

b. Conduct the test, part a, usingα=.10.

c. Find a 90%confidence interval for μd. Interpret this result.

d. What assumptions are necessary to ensure the validity of this analysis?

Short Answer

Expert verified

A confidence interval is explained as the set of numbers seen in our sample for which we anticipate discovering the number that best represents the populace.

Step by step solution

01

Step-by-Step Solution Step 1: (a) State the null and alternate hypotheses

Let μ1and μ2be the means of populations 1 and 2, respectively, and μdbe the difference between the means of two populations.

Null Hypothesis (H0): There is no difference between the two population means.

H0:μd0(μ1μ20)

Alternate Hypothesis (H0): The mean of population 2 is larger than population 1.

Ha:μd<0(μ1μ2<0)

02

(b) Conduct the Test

d¯=dn=3710=3.7

sd=d2(d)2nn1=181(37)2109=44.19=2.2136

Here,n=10

So, the degree of freedom will be =n1=9

α=0.10

From the t-table, the critical value at 10%the level of significance with a degree of freedom 9 is 1.383.

t=d¯sdn=3.72.213610=5.29

|t|=5.29

Since5.29>1.383 so null hypothesis will be rejected. Therefore, it can be concluded that the mean of population 2 is larger than population 1.

03

(c) Form the confidence interval

Here, n=10

So, the degree of freedom will be =n1=9

α=0.10

From the t-table, the critical value at 10%the level of significance with a degree of freedom 9is role="math" localid="1652708493593" 1.383.

The margin of error is,

ME=tα/2(sdn)=(1.833)2.213610=1.2831

The Confidence Interval is,

CI=d¯±ME=(3.7)±(1.2831)=(4.98,2.42)

04

(d) State the assumption

  • A random sample of differences is selected from the target population of differences.
  • The population of differences has an approximately normal distribution.

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Most popular questions from this chapter

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.

Corporate sustainability of CPA firms. Refer to the Business and Society (March 2011) study on the sustainability behaviors of CPA corporations, Exercise 2.23 (p. 83). Recall that the level of support for corporate sustainability (measured on a quantitative scale ranging from 0 to 160 points) was obtained for each of 992 senior managers at CPA firms. The accompanying Minitab printout gives the mean and standard deviation for the level of support variable. It can be shown that level of support is approximately normally distributed.

a. Find the probability that the level of support for corporate sustainability of a randomly selected senior manager is less than 40 points.

b. Find the probability that the level of support for corporate sustainability of a randomly selected senior manager is between 40 and 120 points.

c. Find the probability that the level of support for corporate sustainability of a randomly selected senior manager is greater than 120 points.

d. One-fourth of the 992 senior managers indicated a level of support for corporate sustainability below what value?

Descriptive Statistics: Support

Variables

N

Mean

StDev

Variance

Minimum

Maximum

Range

Support

992

67.755

26.871

722.036

0.000

155.000

155.000

A random sample of n = 6 observations from a normal distribution resulted in the data shown in the table. Compute a 95% confidence interval for σ2

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.

Comparing taste-test rating protocols. Taste-testers of new food products are presented with several competing food samples and asked to rate the taste of each on a 9-point scale (where1="dislike extremely" and9="like extremely"). In the Journal of Sensory Studies (June 2014), food scientists compared two different taste-testing protocols. The sequential monadic (SM) method presented the samples one-at-a-time to the taster in a random order, while the rank rating (RR) method presented the samples to the taster all at once, side-by-side. Consider the following experiment (similar to the one conducted in the journal): 50 consumers of apricot jelly were asked to taste test five different varieties. Half the testers used the SM protocol and half used the RR protocol during testing. In a second experiment, 50 consumers of cheese were asked to taste-test four different varieties. Again, half the testers used the SM protocol and half used the RR protocol during testing. For each product (apricot jelly and cheese), the mean taste scores of the two protocols (SM and RR) were compared. The results are shown in the accompanying tables.

a. Consider the five varieties of apricot jelly. Identify the varieties for which you can conclude that "the mean taste scores of the two protocols (SM and RR) differ significantly atα=.05."

b. Consider the four varieties of cheese. Identify the varieties for which you can conclude that "the mean taste scores of the two protocols (SM and RR) differ significantly atα=.05."

c. Explain why the taste-test scores do not need to be normally distributed for the inferences, parts a and b, to be valid.

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