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Determining Sample Size The sample size needed to estimate the difference between two population proportions to within a margin of error E with a confidence level of 1 - a can be found by using the following expression:

\({\bf{E = }}{{\bf{z}}_{\frac{{\bf{\alpha }}}{{\bf{2}}}}}\sqrt {\frac{{{{\bf{p}}_{\bf{1}}}{{\bf{q}}_{\bf{1}}}}}{{{{\bf{n}}_{\bf{1}}}}}{\bf{ + }}\frac{{{{\bf{p}}_{\bf{2}}}{{\bf{q}}_{\bf{2}}}}}{{{{\bf{n}}_{\bf{2}}}}}} \)

Replace \({{\bf{n}}_{\bf{1}}}\;{\bf{and}}\;{{\bf{n}}_{\bf{2}}}\) by n in the preceding formula (assuming that both samples have the same size) and replace each of \({{\bf{p}}_{\bf{1}}}{\bf{,}}{{\bf{q}}_{\bf{1}}}{\bf{,}}{{\bf{p}}_{\bf{2}}}\;{\bf{and}}\;{{\bf{q}}_{\bf{2}}}\)by 0.5 (because their values are not known). Solving for n results in this expression:

\({\bf{n = }}\frac{{{\bf{z}}_{\frac{{\bf{\alpha }}}{{\bf{2}}}}^{\bf{2}}}}{{{\bf{2}}{{\bf{E}}^{\bf{2}}}}}\)

Use this expression to find the size of each sample if you want to estimate the difference between the proportions of men and women who own smartphones. Assume that you want 95% confidence that your error is no more than 0.03.

Short Answer

Expert verified

The sample size for men and women is 2135.

Step by step solution

01

Given information

The formula for the sample size is given as,

\(n = \frac{{z_{\frac{\alpha }{2}}^2}}{{2{E^2}}}\)

Where, E represents margin of error and\({z_{\frac{\alpha }{2}}}\)is the critical value (two-tailed).

The margin of error is no more than 0.03 and the confidence level is 95% or 0.95.

02

Compute the critical value

The critical value\({z_{\frac{\alpha }{2}}}\)is defined at\(\alpha \)level of significance as,

\(P\left( {Z > {z_{\frac{\alpha }{2}}}} \right) = \frac{\alpha }{2}\)

As the confidence level is 0.95, the significance level is 0.05.

Thus, the critical value is,

\(\begin{array}{c}P\left( {Z > {z_{\frac{{0.05}}{2}}}} \right) = \frac{{0.05}}{2}\\P\left( {Z > {z_{\frac{{0.05}}{2}}}} \right) = 0.025\\1 - P\left( {Z < {z_{0.025}}} \right) = 0.025\\P\left( {Z < {z_{0.025}}} \right) = 0.975\end{array}\)

From the standard normal table, the critical value is hence obtained at the intersection of row 1.9 and column 0.06 which gives the z-score of 1.96.

03

Compute the sample size

Substitute the values in the given formula,

\(\begin{array}{c}n = \frac{{{{1.96}^2}}}{{2{{\left( {0.03} \right)}^2}}}\\ = 2134.22\\ \approx 2135\end{array}\)

Thus, the required sample size for men and women is 2135.

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Most popular questions from this chapter

Testing Claims About Proportions. In Exercises 7โ€“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.

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a. Test the claim using a hypothesis test.

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

c. If the significance level is changed to 0.01, does the conclusion change?

Hypothesis Tests and Confidence Intervals for Hemoglobin

a. Exercise 2 includes a confidence interval. If you use the P-value method or the critical value method from Part 1 of this section to test the claim that women and men have the same mean hemoglobin levels, will the hypothesis tests and the confidence interval result in the same conclusion?

b. In general, if you conduct a hypothesis test using the methods of Part 1 of this section, will the P-value method, the critical value method, and the confidence interval method result in the same conclusion?

c. Assume that you want to use a 0.01 significance level to test the claim that the mean haemoglobin level in women is lessthan the mean hemoglobin level in men. What confidence level should be used if you want to test that claim using a confidence interval?

In Exercises 5โ€“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 โ€œTableโ€ 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 โ€œdebilitating test anxiety,โ€ which most of us call panic or blanking out (based on data from โ€œItem Arrangement, Cognitive Entry Characteristics, Sex and Test Anxiety as Predictors of Achievement in Examination Performance,โ€ 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

We have specified a margin of error, a confidence level, and a likely range for the observed value of the sample proportion. For each exercise, obtain a sample size that will ensure a margin of error of at most the one specified (provided of course that the observed value of the sample proportion is further from 0.5than the educated guess).Obtain a sample size that will ensure a margin of error of at most the one specified.

marginoferror=0.04;confidencelevel=99%;likelyrange=0.7orless

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Subject

A

B

C

D

E

F

G

H

I

J

K

L

Before

200

174

198

170

179

182

193

209

185

155

169

210

After

191

170

177

167

159

151

176

183

159

145

146

177

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