Equivalent Tests A\({\chi ^2}\)test involving a 2\( \times \)2 table is equivalent to the test for the differencebetween two proportions, as described in Section 9-1. Using the claim and table inExercise 9 “Four Quarters the Same as $1?” verify that the\({\chi ^2}\)test statistic and the zteststatistic (found from the test of equality of two proportions) are related as follows:\({z^2}\)=\({\chi ^2}\).

Also show that the critical values have that same relationship.

Short Answer

Expert verified

The critical values and the test statistic of \({\chi ^2}\;{\rm{and}}\;{z^2}\) shows the same relationship; that is \({\chi ^2} = {z^2}\).

Step by step solution

01

Given information

The data for the students, whether they purchased gum or kept the money,is provided.

02

Compute the test statistic

Referring to Exercise 9 of section 11-2,

The value of the chi-square test statistic is 12.162.

From Table A-4, the critical value for the row correspondsto 1 degree of freedom and at 0.05 level of significance 3.841.

Therefore, the critical value is 3.841.

03

Compute the proportions and z test statistic

Let\({\hat p_1}\)representthe sample proportion of students who purchased the gum and students given four quarters.

Let\({\hat p_2}\)representthe sample proportion of students who purchased the gum and students given a $1 Bill.

The proportions are computed as,

\(\begin{aligned}{c}{{\hat p}_1} = \frac{{27}}{{27 + 16}}\\ = 0.628\end{aligned}\)

Similarly,

\(\begin{aligned}{c}{{\hat p}_2} = \frac{{12}}{{12 + 34}}\\ = 0.261\end{aligned}\)

The value of the pooled sample proportion is computed as follows:

\(\begin{aligned}{c}\bar p = \frac{{{x_1} + {x_2}}}{{{n_1} + {n_2}}}\\ = \frac{{12 + 27}}{{46 + 43}}\\ = 0.438\end{aligned}\)

\(\begin{aligned}{c}\bar q = 1 - \bar p\\ = 1 - 0.438\\ = 0.562\end{aligned}\)

The value of the test statistic is computed below:

\(\begin{aligned}{c}z = \frac{{\left( {{{\hat p}_1} - {{\hat p}_2}} \right) - \left( {{p_1} - {p_2}} \right)}}{{\sqrt {\frac{{\bar p\bar q}}{{{n_1}}} + \frac{{\bar p\bar q}}{{{n_2}}}} }}\;\;\;\;{\rm{where}}\left( {{p_1} - {p_2}} \right) = 0\\ = \frac{{\left( {0.261 - 0.628} \right) - 0}}{{\sqrt {\frac{{\left( {0.438} \right)\left( {0.562} \right)}}{{46}} + \frac{{\left( {0.438} \right)\left( {0.562} \right)}}{{43}}} }}\\ = - 3.487395274\end{aligned}\)

Thus, the value of z test statistic is -3.487395274.

The critical value of z corresponding to \(\alpha = 0.05\) for a two-tailed test is equal to \( \pm \)1.96.

04

Show the relationship

The calculations are as follows,

For test statistic:

\(\begin{aligned}{c}{z^2} = {\left( { - 3.487395274} \right)^2}\\ = 12.162\end{aligned}\)

Thus,\({\chi ^2} = {z^2}\)

For critical values:

\(\begin{aligned}{c}{z^2} = {\left( {1.96} \right)^2}\\ = 3.841\end{aligned}\)

Thus,\({\chi ^2} = {z^2}\)

Therefore, the critical value of chi-square and square of z critical value is approximately the same.

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Most popular questions from this chapter

A case-control (or retrospective) study was conductedto investigate a relationship between the colors of helmets worn by motorcycle drivers andwhether they are injured or killed in a crash. Results are given in the table below (based on datafrom “Motorcycle Rider Conspicuity and Crash Related Injury: Case-Control Study,” by Wellset al., BMJ USA,Vol. 4). Test the claim that injuries are independent of helmet color. Shouldmotorcycle drivers choose helmets with a particular color? If so, which color appears best?

Color of helmet


Black

White

Yellow/Orange

Red

Blue

Controls (not injured)

491

377

31

170

55

Cases (injured or killed)

213

112

8

70

26

Cybersecurity When using the data from Exercise 1 to test for goodness-of-fit with the distribution described by Benford’s law, identify the null and alternative hypotheses.

The accompanying table is from a study conducted

with the stated objective of addressing cell phone safety by understanding why we use a particular ear for cell phone use. (See “Hemispheric Dominance and Cell Phone Use,” by Seidman, Siegel, Shah, and Bowyer, JAMA Otolaryngology—Head & Neck Surgery,Vol. 139, No. 5.)

The goal was to determine whether the ear choice is associated with auditory or language brain hemispheric dominance. Assume that we want to test the claim that handedness and cell phone ear preference are independent of each other.

a. Use the data in the table to find the expected value for the cell that has an observed frequency of 3. Round the result to three decimal places.

b. What does the expected value indicate about the requirements for the hypothesis test?

Right Ear

Left Ear

No Preference

Right-Handed

436

166

40

Left-Handed

16

50

3

Cybersecurity The table below lists leading digits of 317 inter-arrival Internet traffic times for a computer, along with the frequencies of leading digits expected with Benford’s law (from Table 11-1 in the Chapter Problem).

a. Identify the notation used for observed and expected values.

b. Identify the observed and expected values for the leading digit of 2.

c. Use the results from part (b) to find the contribution to the\({\chi ^2}\)test statistic from the category representing the leading digit of 2.

Leading Digit

1

2

3

4

5

6

7

8

9

Benford’s

Law

30.1%

17.6%

12.5%

9.7%

7.9%

6.7%

5.8%

5.1%

4.6%

Leading Digits

of Inter-Arrival

Traffic Times

76

62

29

33

19

27

28

21

22

In Exercises 5–20, conduct the hypothesis test and provide the test statistic and the P-value and , or critical value, and state the conclusion.

Testing a Slot Machine The author purchased a slot machine (Bally Model 809) and tested it by playing it 1197 times. There are 10 different categories of outcomes, including no win, win jackpot, win with three bells, and so on. When testing the claim that the observed outcomes agree with the expected frequencies, the author obtained a test statistic of\({\chi ^2} = 8.185\). Use a 0.05 significance level to test the claim that the actual outcomes agree with the expected frequencies. Does the slot machine appear to be functioning as expected?

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