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Confidenhce leagues within FCS, the Patriot League, played 4 games that weekend. Their mean was 8.75. exercise in Chapter 7. we asked whether college foot- ball teams tend to be more likely or less likely to be mismatched in the a. Calculate the 95% confidence interval for this sample. National Collegiate Athletic b. State in your own words what we learn from this confidence interval. upper Association (NCAA) divisions. During one week of a college football scason, the population of 53 Toot- ball Bowl Subdivision (FBS) games had a mean spread (winning score minus losing score) of 16.189, with a standard deviation of 12.128. We took a sample of 4 games that were played that week in the next-highest league, the Football Championship Subdivision (FCS). to see if the spread were different: one of the many c. What information does the confidence interval give us that we also get from a hypothesis test? d. What additional information does the confidence interval give us that we do not get from a hypoth- esis test? 8.50 Confidence intervals and football wins (contin- ued): Using the football data presented in Exercise 8.49, practice evaluating data using confidence intervals. a. Compute the 80% confidence interval, b. How do the conclusion and the confidence interval change as you move from 95% confidence to 80% confidence? c. Why don't we talk about having 100% confidence?

Confidenhce leagues within FCS, the Patriot League, played 4 games that weekend. Their mean was 8.75. exercise in Chapter 7. we asked whether college foot- ball teams tend to be more likely or less likely to be mismatched in the a. Calculate the 95% confidence interval for this sample. National Collegiate Athletic b. State in your own words what we learn from this confidence interval. upper Association (NCAA) divisions. During one week of a college football scason, the population of 53 Toot- ball Bowl Subdivision (FBS) games had a mean spread (winning score minus losing score) of 16.189, with a standard deviation of 12.128. We took a sample of 4 games that were played that week in the next-highest league, the Football Championship Subdivision (FCS). to see if the spread were different: one of the many c. What information does the confidence interval give us that we also get from a hypothesis test? d. What additional information does the confidence interval give us that we do not get from a hypoth- esis test? 8.50 Confidence intervals and football wins (contin- ued): Using the football data presented in Exercise 8.49, practice evaluating data using confidence intervals. a. Compute the 80% confidence interval, b. How do the conclusion and the confidence interval change as you move from 95% confidence to 80% confidence? c. Why don't we talk about having 100% confidence?

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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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8.49 Confidence intervals and football wins: In an leagues within FCS, the Patriot League, played4 games that weekend. Their mean was 8.75. exercise in Chapter 7. we asked whether college foot- ball teams tend to be more likely or less likely to be mismatched in the upper National Collegiate Athletic Association (NCAA) divisions. During one week of a college football season, the population of 53 Toot- ball Bowl Subdivision (FBS) games had a mean spread (winning score minus losing score) of 16.189, with a standard deviation of 12.128. We took a sample of4 games that were played that week in the next-highest league, the Football Champiornship Subdivision (FCS). to see if the spread were different; one of the many a. Calculate the 95% confidence interval for this sample. b. State in your own words what we learn from this confidence interval. c. What information does the confidence interval give us that we also get from a hypothesis test? d. What additional information does the confidence interval give us that we do not get from a hypoth- esis test? 8.50 Confidence intervals and football wins (contin- ued): Using the football data presented in Exercise 8.49, practice evaluating data using confidence intervals. a. Compute the 80% confidence interval. b. How do the conclusion and the confidence interval change as you move from 95% confidence to 80% confidence? Why don't we talk about having 100% confidence?
Transcribed Image Text:8.49 Confidence intervals and football wins: In an leagues within FCS, the Patriot League, played4 games that weekend. Their mean was 8.75. exercise in Chapter 7. we asked whether college foot- ball teams tend to be more likely or less likely to be mismatched in the upper National Collegiate Athletic Association (NCAA) divisions. During one week of a college football season, the population of 53 Toot- ball Bowl Subdivision (FBS) games had a mean spread (winning score minus losing score) of 16.189, with a standard deviation of 12.128. We took a sample of4 games that were played that week in the next-highest league, the Football Champiornship Subdivision (FCS). to see if the spread were different; one of the many a. Calculate the 95% confidence interval for this sample. b. State in your own words what we learn from this confidence interval. c. What information does the confidence interval give us that we also get from a hypothesis test? d. What additional information does the confidence interval give us that we do not get from a hypoth- esis test? 8.50 Confidence intervals and football wins (contin- ued): Using the football data presented in Exercise 8.49, practice evaluating data using confidence intervals. a. Compute the 80% confidence interval. b. How do the conclusion and the confidence interval change as you move from 95% confidence to 80% confidence? Why don't we talk about having 100% confidence?
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