{"id":264809,"date":"2026-07-15T02:28:02","date_gmt":"2026-07-14T23:28:02","guid":{"rendered":"https:\/\/1kitap1.com\/en\/introduction-to-statistics-george-woodbury\/"},"modified":"2026-07-15T02:28:02","modified_gmt":"2026-07-14T23:28:02","slug":"introduction-to-statistics-george-woodbury","status":"publish","type":"post","link":"https:\/\/1kitap1.com\/en\/introduction-to-statistics-george-woodbury\/","title":{"rendered":"Introduction To Statistics – George Woodbury"},"content":{"rendered":"
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Here is an example for which we will construct a confidence interval. 6.30 A company that makes a drug to reverse hair loss in males claims that 60% of the men who try their drug will grow new hair. A test on 40 randomly selected males experiencing hair loss produced the following results (Yes = grew new hair; No = no new hair). Yes No No No Yes No No No Yes No Yes Yes Yes Yes No No Yes No Yes Yes Yes Yes Yes Yes No Yes Yes Yes No No No Yes No No Yes Yes No Yes No Yes Construct a 95% confidence interval for the proportion of all men experiencing hair loss that will grow new hair by taking this drug.<\/p>\n

Begin by pressing STAT , and moving to the TESTS menu. Select option A: 1-PropZInt. Next to x: enter the number of successes (22). Next to n: enter the sample size (40). After entering the level of confidence, highlight Calculate and press ENTER . Here is the screen that you will see. The confidence interval is 0.39583 \u2264\u03c0 \u2264 0.70417. \u25a0 Appropriate Sample Size We can determine how large our sample needs to be for estimating a population pro- portion just as we did for estimating a population mean.<\/p>\n

We begin with the formula for margin of error, and solve for n. p \u2022 (1 \u2013 p) E = z\u03b1\/2 \u2022\u0002\u0002\u0002 n p \u2022 (1 \u2013 p) 2 = \u0002 \u0006z\u03b1\/2 \u2022\u0002\u0002\u0003 \u0003 n \u0007 p \u2022 (1 \u2013 p) \u2022 \u0002\u0002 z\u03b1\/2 n p \u2022 (1 \u2013 p) E2 \u2022 n = \u2022 \u0002\u0002 \u2022 n n z\u03b1\/2 \u0002 \u0002 CHAPTER 6 The Central Limit Theorem and Confidence Intervals E2 \u2022 n = z\u03b1\/2 \u2022 p \u2022 (1 \u2013 p) E2 \u2022 n z\u03b1\/2 \u2022 p \u2022 (1 \u2013 p) \u0002\u0002 = \u0002\u0002\u0002 z\u03b1\/2 2 \u2022 p \u2022 (1 \u2013 p) n = \u0002\u0002\u0002 z\u03b1\/2 2 n = \u0002\u0002 \u2022 p \u2022 (1 \u2013 p) The formula for the appropriate sample size to estimate a proportion is z\u03b1\/2 2 n = \u0002\u0002 \u2022 p \u2022 (1 \u2013 p) If there is no estimate of the sample proportion given, then we replace p by 0.5.<\/p>\n

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The Law of Large Numbers 159 Binomial Probabilities through Simulation 198 Generating Random Normal Data 233 Investigating the Normal Approximation 244 Central Limit Theorem 270 Confidence Intervals 285 Confidence Intervals for Population Proportions 309 The Effect of Sample Size 337 p-Values 363 Mini-Projects An opportunity to learn about your fellow classmates 16 Fellow classmates: frequency distributions, histograms, and pie charts 45 Fellow classmates: mean, median, first quartile, third quartile, midrange, and mode 73 Fellow classmates: range, interquartile range, and standard deviation 103 Probability that a randomly selected student on your campus is female 162 The mean age of students at your school 285 The mean number of units taken by students at your school this term 296 Proportion of all vehicles in your school\u2019s parking lots that are convertibles 308 Testing the claim that the mean height for adult females is 5\u0002 5\u0003 337 Testing the claim that the mean height for adult males is 5\u0002 9\u0003 352 Testing the claim that more than 50% of students at your school are female 363 Have college males and females had the same mean number of serious relationships?<\/p>\n

393 The amount of money your classmates spent in the last week on food 408 Weight students have gained or lost since attending your school 425 Do students at your school approve of the job the president is doing? 439 Hours per week study time of students at your school 454 Number of calories in one serving of several brands of soda, beer, and juice 477 Eye color in a random sample of at least 100 students 494 Gender and eyeglasses in a random sample of at least 100 students 508 Shoe size and height in a random sample of male and female students 564 Research project: start to finish 649 An Introduction to Statistics This page intentionally left blank An Introduction to Statistics George Woodbury College of the Sequoias Australia \u2022 Canada \u2022 Mexico \u2022 Singapore \u2022 Spain \u2022 United Kingdom \u2022 United States Sponsoring Editor: Carolyn Crockett Editorial Assistant: Jennifer Jenkins Assistant Editor: Ann Day Marketing: Tom Ziolkowski\/Samantha Cabaluna Production Editor: Tessa Avila Production Service: Helen Walden Manuscript Editor: Helen Walden COPYRIGHT \u00a9 2002 Wadsworth Group.<\/p>\n

Duxbury is an imprint of the Wadsworth Group, a division of Thomson Learning, Inc. Thomson Learning\u2122 is a trademark used herein under license. ALL RIGHTS RESERVED. No part of this work cov- ered by the copyright hereon may be reproduced or used in any form or by any means\u2014graphic, electronic, or mechanical, including photocopy- ing, recording, taping, Web distribution, or infor- mation storage and retrieval systems\u2014without the prior written permission of the publisher. Printed in Canada.<\/p>\n<\/blockquote>\n

This is a short excerpt from the opening of “” by Unknown, quoted for review and introduction purposes. All rights belong to the copyright holders.<\/em><\/p>\n

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