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Coke and Diet Coke Data Set 26 “Cola Weights and Volumes” in Appendix B includes theweights (in pounds) of cola for a sample of cans of regular Coke (n = 36, \(\bar x\)= 0.81682 lb,s = 0.00751 lb) and the weights of cola for a sample of cans of Diet Coke (n = 36, \(\bar x\) =0.78479 lb, s = 0.00439 lb). Use a 0.05 significance level to test the claim that variation is thesame for both types of Coke.

Short Answer

Expert verified

There is sufficient evidence to reject the claim that the population variance of the regular coke group is different from the population variance of the diet coke group.

Step by step solution

01

Given information

For a sample of 36 cans of regular Coke, the mean weight of cola is equal to 0.81682 lb, and the standard deviation is equal to 0.00751 lb. For another sample of 36 cans of Diet Coke, the mean weight of cola is equal to 0.78479 lb,and the standard deviation is equal to 0.00439 lb.

It is claimed that the variation in the amount of cola for the regular Coke is equal to the variation in the amount of Cola for the Diet Coke.

02

Hypotheses

Let\({\sigma _1}\)and\({\sigma _2}\)be the population standard deviations of the weight of colafor the regular Coke and the Diet Cokerespectively.

Null Hypothesis:The populationstandard deviationof the weight of colafor the regular Cokeis equal to the population standard deviation of the weight of colafor the Diet Coke.

Symbolically,

\({H_0}:{\sigma _1} = {\sigma _2}\)

Alternative Hypothesis:The populationstandard deviationof the weight of colafor the regular Cokeis not equal to the population standard deviationof the weight of colafor the Diet Coke.

Symbolically,

\({H_1}:{\sigma _1} \ne {\sigma _2}\)

03

Compute the test statistic

Since two independent samples involve a claim about the population standard deviation, apply an F-test.

Consider the larger sample variance to be\(s_1^2\)and the corresponding sample size to be\({n_1}\).

The following values are obtained:

\({\left( {0.00751} \right)^2} = 0.000056\)

\({\left( {0.00439} \right)^2} = 0.000019\)

Here,\(s_1^2\)is the sample variance corresponding to the regular Coke has a value equal to 0.000056 lb squared.

\(s_2^2\)is the sample variance corresponding to the Diet Cokeand has a value equal to 0.000019 lb squared.

Substitute the respective values to calculate the F statistic:

\(\begin{array}{c}F = \frac{{{{\left( {0.00751} \right)}^2}}}{{{{\left( {0.00439} \right)}^2}}}\\ = 2.927\end{array}\)

Thus, F is equal to 2.927.

04

Critical value and p-value

The value of the numerator degrees of freedom is equal to:

\(\begin{array}{c}{n_1} - 1 = 36 - 1\\ = 35\end{array}\)

The value of the denominator degrees of freedom is equal to:

\(\begin{array}{c}{n_2} - 1 = 36 - 1\\ = 35\end{array}\)

For the F test, the critical value corresponding to the right-tail is considered.

The critical value can be obtained using the F-distribution table with numerator degrees of freedom equal to 35 and denominator degrees of freedom equal to 35 for a right-tailed test.

The level of significance is equal to:

\(\begin{array}{c}\frac{\alpha }{2} = \frac{{0.05}}{2}\\ = 0.025\end{array}\)

Thus, the critical value is equal to 1.9611.

The two-tailed p-value for F equal to 2.927 is equal to 0.0020.

05

Conclusion

Since the test statistic value is greater than the critical value and the p-value is less than 0.05, the null hypothesis is rejected.

Thus, there is enough evidence to rejectthe claimthat variation is the same for both types of Coke.

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Most popular questions from this chapter

In Exercises 5–20, assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. (Note: Answers in Appendix D include technology answers based on Formula 9-1 along with “Table” answers based on Table A-3 with df equal to the smaller of n1−1 and n2−1.)

Color and Cognition Researchers from the University of British Columbia conducted a study to investigate the effects of color on cognitive tasks. Words were displayed on a computer screen with background colors of red and blue. Results from scores on a test of word recall are given below. Higher scores correspond to greater word recall.

a. Use a 0.05 significance level to test the claim that the samples are from populations with the same mean.

b. Construct a confidence interval appropriate for the hypothesis test in part (a). What is it about the confidence interval that causes us to reach the same conclusion from part (a)?

c. Does the background color appear to have an effect on word recall scores? If so, which color appears to be associated with higher word memory recall scores?

Red Background n = 35, x = 15.89, s = 5.90

Blue Background n = 36, x = 12.31, s = 5.48

Testing Claims About Proportions. In Exercises 7–22, test the given claim. Identify the null hypothesis, alternative hypothesis, test statistic, P-value or critical value(s), then state the conclusion about the null hypothesis, as well as the final conclusion that addresses the original claim.

Tennis Challenges Since the Hawk-Eye instant replay system for tennis was introduced at the U.S. Open in 2006, men challenged 2441 referee calls, with the result that 1027 of the calls were overturned. Women challenged 1273 referee calls, and 509 of the calls were overturned. We want to use a 0.05 significance level to test the claim that men and women have equal success in challenging calls.

a. Test the claim using a hypothesis test.

b. Test the claim by constructing an appropriate confidence interval.

c. Based on the results, does it appear that men and women have equal success in challenging calls?

In Exercises 5–20, assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. (Note: Answers in Appendix D include technology answers based on Formula 9-1 along with “Table” answers based on Table A-3 with df equal to the smaller of\({n_1} - 1\)and\({n_2} - 1\).)

Are Male Professors and Female Professors Rated Differently?

a. Use a 0.05 significance level to test the claim that two samples of course evaluation scores are from populations with the same mean. Use these summary statistics: Female professors:

n = 40, \(\bar x\)= 3.79, s = 0.51; male professors: n = 53, \(\bar x\) = 4.01, s = 0.53. (Using the raw data in Data Set 17 “Course Evaluations” will yield different results.)

b. Using the summary statistics given in part (a), construct a 95% confidence interval estimate of the difference between the mean course evaluations score for female professors and male professors.

c. Example 1 used similar sample data with samples of size 12 and 15, and Example 1 led to the conclusion that there is not sufficient evidence to warrant rejection of the null hypothesis.

Do the larger samples in this exercise affect the results much?

Denomination Effect In the article “The Denomination Effect” by Priya Raghubir and Joydeep Srivastava, Journal of Consumer Research, Vol. 36, researchers reported results from studies conducted to determine whether people have different spending characteristics when they have larger bills, such as a \(20 bill, instead of smaller bills, such as twenty \)1 bills. In one trial, 89 undergraduate business students from two different colleges were randomly assigned to two different groups. In the “dollar bill” group, 46 subjects were given dollar bills; the “quarter” group consisted of 43 subjects given quarters. All subjects from both groups were given a choice of keeping the money or buying gum or mints. The article includes the claim that “money in a large denomination is less likely to be spent relative to an equivalent amount in smaller denominations.” Test that claim using a 0.05 significance level with the following sample data from the study.

In Exercises 5–20, assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. (Note: Answers in Appendix D include technology answers based on Formula 9-1 along with “Table” answers based on Table A-3 with df equal to the smaller of\({n_1} - 1\)and\({n_2} - 1\).)Blanking Out on Tests Many students have had the unpleasant experience of panicking on a test because the first question was exceptionally difficult. The arrangement of test items was studied for its effect on anxiety. The following scores are measures of “debilitating test anxiety,” which most of us call panic or blanking out (based on data from “Item Arrangement, Cognitive Entry Characteristics, Sex and Test Anxiety as Predictors of Achievement in Examination Performance,” by Klimko, Journal of Experimental Education, Vol. 52, No. 4.) Is there sufficient evidence to support the claim that the two populations of scores have different means? Is there sufficient evidence to support the claim that the arrangement of the test items has an effect on the score? Is the conclusion affected by whether the significance level is 0.05 or 0.01?

Questions Arranged from Easy to Difficult

24.64

39.29

16.32

32.83

28.02

33.31

20.60

21.13

26.69

28.9

26.43

24.23

7.10

32.86

21.06

28.89

28.71

31.73

30.02

21.96

25.49

38.81

27.85

30.29

30.72

Questions Arranged from Difficult to Easy

33.62

34.02

26.63

30.26

35.91

26.68

29.49

35.32

27.24

32.34

29.34

33.53

27.62

42.91

30.20

32.54

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