F Test If using the sample data in Data Set 1 “Body Data” in Appendix B for a test of the claim that heights of men and heights of women have different variances, we find that s= 7.48296 cm for women and s= 7.10098 cm for men.

a. Find the values \(s_1^2\) and \(s_2^2\) express them with appropriate units of measure.

b. Identify the null and alternative hypotheses.

c. Find the value of the Ftest statistic and round it to four decimal places.

d. The P-value for this test is 0.5225. What do you conclude about the stated claim?

Short Answer

Expert verified

a.The value of \(s_1^2\) is equal to 55.99469 cm squared, and the value of \(s_2^2\) is equal to 50.42392 cm squared.

b. Null Hypothesis: The variance of the heights of women is equal to the variance of the heights of men.

Alternative Hypothesis: The variance of the heights of women is not equal to the variance of the heights of men.

c. The F-statistic is equal to 1.1105.

d. There is not sufficient evidence to support the claim that heights of men and heights of women have different variances

Step by step solution

01

Given information

The sample standard deviation of the heights of men is equal to 7.10098 cm. The sample standard deviation of the heights of women is 7.48296 cm.

02

Find the values of the sample variances

In general, the larger of the two sample variances is denoted by \(s_1^2\) while, the smaller of the two sample variances is denoted by \(s_2^2\).

Here, the values of the sample variances are computed as shown:

\(\begin{array}{c}{s^2}_{women} = {\left( {7.48296} \right)^2}\\ = 55.99469\end{array}\)

\(\begin{array}{c}{s^2}_{men} = {\left( {7.10098} \right)^2}\\ = 50.42392\end{array}\)

It can be observed that the sample variance corresponding to the heights of women is greater than the sample variance corresponding to the heights of men.

Thus, \(s_1^2 = 55.99469\;{\rm{c}}{{\rm{m}}^{\rm{2}}}\) and \(s_2^2 = 50.42392\;{\rm{c}}{{\rm{m}}^{\rm{2}}}\).

03

State the hypotheses

b.

To test the significance of the claim that the variances of the heights of women and men are not equal, the hypotheses are formulated as follows:

Null Hypothesis: The variance of the heights of women is equal to the variance of the heights of men.

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

Alternative Hypothesis: The variance of the heights of women is not equal to the variance of the heights of men.

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

04

State the test statistic

c.

The value of the test statistic is computed as follows:

\(\begin{array}{c}F = \frac{{s_1^2}}{{s_2^2}}\\ = \frac{{55.99469}}{{50.42392}}\\ = 1.1105\end{array}\)

Thus, the F-statistic is equal to 1.1105.

05

Conclusion of the claim

d.

The level of significance assumed is equal to 0.05.

The p-value is equal to 0.5225, which is greater than 0.05. So, the null hypothesis is failed to reject.

Therefore, there is not sufficient evidence to support the claim that heights of men and heights of women have different variances

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Notation for the sample data given in exercise 1, consider the salk vaccine treatment group to be the first sample. Identify the values of \({{\bf{n}}_{\bf{1}}}{\bf{,}}{{\bf{\hat p}}_{\bf{1}}}{\bf{,}}{{\bf{\hat q}}_{\bf{1}}}{\bf{,}}{{\bf{n}}_{\bf{2}}}{\bf{,}}{{\bf{\hat p}}_{\bf{2}}}{\bf{,}}{{\bf{\hat q}}_{\bf{2}}}{\bf{,\bar p}}\) and \({\bf{\bar q}}\). Round all values so that they have six significant digits.

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 Creativity Researchers from the University of British Columbia conducted trials to investigate the effects of color on creativity. Subjects with a red background were asked to think of creative uses for a brick; other subjects with a blue background were given the same task. Responses were scored by a panel of judges and results from scores of creativity are given below. Higher scores correspond to more creativity. The researchers make the claim that “blue enhances performance on a creative task.”

a. Use a 0.01 significance level to test the claim that blue enhances performance on a creative task.

b. Construct the 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)?

Red Background: n = 35, x = 3.39, s = 0.97

Blue Background: n = 36, x = 3.97, s = 0.63

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.

Lefties In a random sample of males, it was found that 23 write with their left hands and 217 do not. In a random sample of females, it was found that 65 write with their left hands and 455 do not (based on data from “The Left-Handed: Their Sinister History,” by ElaineFowler Costas, Education Resources Information Center, Paper 399519). We want to use a 0.01significance level to test the claim that the rate of left-handedness among males is less than that among females.

a. Test the claim using a hypothesis test.

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

c. Based on the results, is the rate of left-handedness among males less than the rate of left-handedness among females?

Does Aspirin Prevent Heart Disease? In a trial designed to test the effectiveness of aspirin in preventing heart disease, 11,037 male physicians were treated with aspirin and 11,034 male physicians were given placebos. Among the subjects in the aspirin treatment group, 139 experienced myocardial infarctions (heart attacks). Among the subjects given placebos, 239 experienced myocardial infarctions (based on data from “Final Report on the Aspirin Component of the Ongoing Physicians’ Health Study,” New England Journal of Medicine, Vol. 321: 129–135). Use a 0.05 significance level to test the claim that aspirin has no effect on myocardial infarctions.

a. Test the claim using a hypothesis test.

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

c. Based on the results, does aspirin appear to be effective?

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?

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free