Notation for the sample data given in exercise 1, consider the salk vaccine treatment group to be the first sample. Identify the values of n1,p^1,q^1,n2,p^2,q^2,p¯and q¯. Round all values so that they have six significant digits.

Short Answer

Expert verified

The values of notations are as follows:

n1=201,229p^1=0.000164q^1=0.999836n2=200745

p^2=0.000573q^2=0.999427p¯=0.000368q¯=0.999632

Step by step solution

01

Step-1: Given information

The study is conducted on 401974 children divided into two groups:

Treatment: Of 201229, 33 developed polio.

Placebo: Of 200,745, 115 developed polio.

02

Step-2: Interpretation of notations in two proportions test

The general notations are expressed as,

n1=size of first sample

n2=size of second sample

p^1=sample proportion of success in first sample

q^1=complement of sample successes in second sample.

p^2=sample proportion of success in second sample

q^2=complement of sample successes in first sample

p¯=pooled sample proportion

q¯=1-p¯

03

Step-3: Identify the values from the given information

Let the treatment group be defined as group 1 and Placebo as group 2.

Then,

n1=201229x1=33n2=200745x2=115

04

Step-4:  Compute measure of sample proportions 

Sample proportions are calculated as,

p^1=x1n1=33201229=0.000164

q^1=1-p^1=1-0.000164=0.999836

Similarly,

p^2=x2n2=115200745=0.000573

q^2=1-p^2=1-0.000573=0.999427

05

Find sample pooled proportion 

Now, the pooled sample proportion can be calculated as,

p¯=x1+x2n1+n2=33+115201229+200745=0.000368

Complement of pooled sample proportion can be calculated as,

q¯=1-p¯=1-0.000368=0.999632

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

Degrees of FreedomIn Exercise 20 “Blanking Out on Tests,” using the “smaller of\({n_1} - 1\) and \({n_2} - 1\)” for the number of degrees of freedom results in df = 15. Find the number of degrees of freedom using Formula 9-1. In general, how are hypothesis tests and confidence intervals affected by using Formula 9-1 instead of the “smaller of \({n_1} - 1\)and \({n_2} - 1\)”?

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.

Overlap of Confidence Intervals In the article “On Judging the Significance of Differences by Examining the Overlap Between Confidence Intervals,” by Schenker and Gentleman (American Statistician, Vol. 55, No. 3), the authors consider sample data in this statement: “Independent simple random samples, each of size 200, have been drawn, and 112 people in the first sample have the attribute, whereas 88 people in the second sample have the attribute.”

a. Use the methods of this section to construct a 95% confidence interval estimate of the difference\({p_1} - {p_2}\). What does the result suggest about the equality of \({p_1}\) and \({p_2}\)?

b. Use the methods of Section 7-1 to construct individual 95% confidence interval estimates for each of the two population proportions. After comparing the overlap between the two confidence intervals, what do you conclude about the equality of \({p_1}\) and \({p_2}\)?

c. Use a 0.05 significance level to test the claim that the two population proportions are equal. What do you conclude?

d. Based on the preceding results, what should you conclude about the equality of \({p_1}\) and \({p_2}\)? Which of the three preceding methods is least effective in testing for the equality of \({p_1}\) and \({p_2}\)?

Independent and Dependent Samples Which of the following involve independent samples?

a. Data Set 14 “Oscar Winner Age” in Appendix B includes pairs of ages of actresses and actors at the times that they won Oscars for Best Actress and Best Actor categories. The pair of ages of the winners is listed for each year, and each pair consists of ages matched according to the year that the Oscars were won.

b. Data Set 15 “Presidents” in Appendix B includes heights of elected presidents along with the heights of their main opponents. The pair of heights is listed for each election.

c. Data Set 26 “Cola Weights and Volumes” in Appendix B includes the volumes of the contents in 36 cans of regular Coke and the volumes of the contents in 36 cans of regular Pepsi.

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\({n_2} - 1\).)

Seat Belts A study of seat belt use involved children who were hospitalized after motor vehicle crashes. For a group of 123 children who were wearing seat belts, the number of days in intensive care units (ICU) has a mean of 0.83 and a standard deviation of 1.77. For a group of 290 children who were not wearing seat belts, the number of days spent in ICUs has a mean of 1.39 and a standard deviation of 3.06 (based on data from “Morbidity Among Pediatric Motor Vehicle Crash Victims: The Effectiveness of Seat Belts,” by Osberg and Di Scala, American Journal of Public Health, Vol. 82, No. 3).

a. Use a 0.05 significance level to test the claim that children wearing seat belts have a lower mean length of time in an ICU than the mean for children not wearing seat belts.

b. Construct a confidence interval appropriate for the hypothesis test in part (a).

c. What important conclusion do the results suggest?

Using Confidence Intervals

a. Assume that we want to use a 0.05 significance level to test the claim that p1 < p2. Which is better: A hypothesis test or a confidence interval?

b. In general, when dealing with inferences for two population proportions, which two of the following are equivalent: confidence interval method; P-value method; critical value method?

c. If we want to use a 0.05 significance level to test the claim that p1 < p2, what confidence level should we use?

d. If we test the claim in part (c) using the sample data in Exercise 1, we get this confidence interval: -0.000508 < p1 - p2 < - 0.000309. What does this confidence interval suggest about the claim?

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