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Questions 6–10 refer to the sample data in the following table, which describes the fate of the passengers and crew aboard the Titanic when it sank on April 15, 1912. Assume that the data are a sample from a large population and we want to use a 0.05 significance level to test the claim that surviving is independent of whether the person is a man, woman, boy, or girl.


Men

Women

Boys

Girls

Survived

332

318

29

27

Died

1360

104

35

18

Is the hypothesis test left-tailed, right-tailed, or two-tailed?

Short Answer

Expert verified

The given hypothesis test is right-tailed.

Step by step solution

01

Given information

A contingency table is constructed that shows the number of passengers who survived/died according to whether they were male, female, boy or girl.

02

Tail of the test

It is known that the tests of independence with a contingency table are always right-tailed.

In the test of independence of attributes, the chi-square test statistic is as follows:

\({\chi ^2} = \sum {\frac{{{{\left( {O - E} \right)}^2}}}{E}} \)

Suppose the discrepancy between the observed and expected frequencies is considerable. In that case, the test statistic value will shift to the right side of the curve, indicating the rejection of the null hypothesis (if it exceeds a certain value). Also, a large deviation means that the observed frequencies do not match the expected frequencies and the two attributes are not independent.

Furthermore, if the difference between the observed and the expected frequencies is less, the test statistic value will shift to the left side of the curve, implying that the given frequencies match the expected frequencies. As a result, the two attributes will be independent.

The claim to be tested is that the passenger’s survival is independent of whether the person is a man, woman, boy or a girl.

This implies that it is the independence of attributes test.

Therefore, the given hypothesis test is said to be a right-tailed test.

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Most popular questions from this chapter

Bias in Clinical Trials? Researchers investigated the issue of race and equality of access to clinical trials. The following table shows the population distribution and the numbers of participants in clinical trials involving lung cancer (based on data from “Participation in Cancer Clinical Trials,” by Murthy, Krumholz, and Gross, Journal of the American Medical Association, Vol. 291, No. 22). Use a 0.01 significance level to test the claim that the distribution of clinical trial participants fits well with the population distribution. Is there a race/ethnic group that appears to be very underrepresented?

Race/ethnicity

White

non-Hispanic

Hispanic

Black

Asian/

Pacific

Islander

American Indian/

Alaskan Native

Distribution of

Population

75.6%

9.1%

10.8%

3.8%

0.7%

Number in Lung

Cancer Clinical Trials

3855

60

316

54

12

In a study of high school students at least 16 years of age, researchers obtained survey results summarized in the accompanying table (based on data from “Texting While Driving and Other Risky Motor Vehicle Behaviors Among U.S. High School Students,” by O’Malley, Shults, and Eaton, Pediatrics,Vol. 131, No. 6). Use a 0.05 significance level to

test the claim of independence between texting while driving and driving when drinking alcohol. Are those two risky behaviors independent of each other?


Drove when drinking Alcohol?


Yes

No

Texted while driving

731

3054

No Texting while driving

156

4564

Is the hypothesis test described in Exercise 1 right tailed, left-tailed, or two-tailed? Explain your choice.

Weather-Related Deaths Review Exercise 5 involved weather-related U.S. deaths. Among the 450 deaths included in that exercise, 320 are males. Use a 0.05 significance level to test the claim that among those who die in weather-related deaths, the percentage of males is equal to 50%. Provide an explanation for the results.

Questions 6–10 refer to the sample data in the following table, which describes the fate of the passengers and crew aboard the Titanic when it sank on April 15, 1912. Assume that the data are a sample from a large population and we want to use a 0.05 significance level to test the claim that surviving is independent of whether the person is a man, woman, boy, or girl.


Men

Women

Boys

Girls

Survived

332

318

29

27

Died

1360

104

35

18

What distribution is used to test the stated claim (normal, t, F, chi-square, uniform)?

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