Suppose a veterinarian wants to estimate the difference between the proportion of cat owners who are single and the proportion of dog owners who are single. Of the pet owners that visit any of the veterinarian clinics in her city regularly, she identifies 3872 pet owners that exclusively have cats and 4108 pet owners that exclusively have dogs. From this list of pet owners, she surveys 158 randomly selected cat owners and 139 randomly selected dog owners and asks each of them if they are single or married. Her findings are summarized in the table. Population Population description Sample size Number of successes Sample proportion 1 cat owners ?1=158 ?1=63 ?̂1=0.39873 2 dog owners ?2=139 ?2=52 ?̂2=0.37410 Calculate the upper and lower limits (bounds) for a large sample 90% ?‑confidence interval for the difference in two population proportions, ?1−?2. Give each of your answers with three decimal places of precision.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 10CYU
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Suppose a veterinarian wants to estimate the difference between the proportion of cat owners who are single and the proportion of dog owners who are single. Of the pet owners that visit any of the veterinarian clinics in her city regularly, she identifies 3872 pet owners that exclusively have cats and 4108 pet owners that exclusively have dogs. From this list of pet owners, she surveys 158 randomly selected cat owners and 139 randomly selected dog owners and asks each of them if they are single or married. Her findings are summarized in the table.

Population Population
description
Sample
size
Number
of successes
Sample
proportion
1 cat owners ?1=158 ?1=63 ?̂1=0.39873
2 dog owners ?2=139 ?2=52 ?̂2=0.37410

Calculate the upper and lower limits (bounds) for a large sample 90% ?‑confidence interval for the difference in two population proportions, ?1−?2. Give each of your answers with three decimal places of precision.                                 

 
 
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