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Section I: Multiple Choice Select the best answer for each question. We compute the

Chapter 11, Problem T11.5

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QUESTION:

Section I: Multiple Choice Select the best answer for each question.

Exercises T11.4 to T11.6 refer to the following setting. A random sample of traffic tickets given to motorists in a large city is examined. The tickets are classified according to the race of the driver. The results are summarized in the following table.

The proportion of this city’s population in each of the racial categories listed above is as follows:

We wish to test \(H_{0}\): The racial distribution of traffic tickets in the city is the same as the racial distribution of the city’s population.

We compute the value of the \(\chi^{2}\) statistic to be 6.58. Assuming that the conditions for inference are met, the P-value of our test is

(a) greater than 0.20.                        (d) between 0.01 and 0.05.

(b) between 0.10 and 0.20.               (e) less than 0.01.

(c) between 0.05 and 0.10.

Questions & Answers

QUESTION:

Section I: Multiple Choice Select the best answer for each question.

Exercises T11.4 to T11.6 refer to the following setting. A random sample of traffic tickets given to motorists in a large city is examined. The tickets are classified according to the race of the driver. The results are summarized in the following table.

The proportion of this city’s population in each of the racial categories listed above is as follows:

We wish to test \(H_{0}\): The racial distribution of traffic tickets in the city is the same as the racial distribution of the city’s population.

We compute the value of the \(\chi^{2}\) statistic to be 6.58. Assuming that the conditions for inference are met, the P-value of our test is

(a) greater than 0.20.                        (d) between 0.01 and 0.05.

(b) between 0.10 and 0.20.               (e) less than 0.01.

(c) between 0.05 and 0.10.

ANSWER:

Step 1 of 3

Given:

The variable race contains 4 categories: White, Black, Hispanic and Other

The degrees of freedom is the number of categories decreased by 1 :

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