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TEST ITEM FILE Pin Ng Northern Arizona University BUSINESS STATISTICS A FIRST COURSE 5e David M. Levine Timothy C. Krehbiel Mark L. Berenson Upper Saddle River, New Jersey 07458 VP/Editorial Director: Sally Yagan Acquisitions Editor: Mark Pfaltzgraff Assistant Editor: Susie Abraham Production Editor: Kerri Tomasso Buyer: Benjamin Smith Copyright © 2008 by Pearson Education, Inc., Upper Saddle River, New Jersey, 07458. Pearson Prentice Hall. All rights reserved. Printed in the United States of America. This publication is protected by Copyright and permission should be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. For information regarding permission(s), write to: Rights and Permissions Department. This work is protected by United States copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning. Dissemination or sale of any part of this work (including on the World Wide Web) will destroy the integrity of the work and is not permitted. The work and materials from it should never be made available to students except by instructors using the accompanying text in their classes. All recipients of this work are expected to abide by these restrictions and to honor the intended pedagogical purposes and the needs of other instructors who rely on these materials. Pearson Prentice HallTM is a trademark of Pearson Education, Inc. 10 9 8 7 6 5 4 3 2 1 ISBN-13: 978-0-13-606581-4 ISBN-10: 0-13-606581-3 ii Table of Contents Preface vii Keywords Index ix Chapter 1 Introduction and Data Collection 1 Chapter 2 Presenting Data in Tables and Charts 29 Chapter 3 Numerical Descriptive Measures 74 Chapter 4 Basic Probability 101 Chapter 5 Discrete Probability Distributions 136 Chapter 6 The Normal Distribution 162 Chapter 7 Sampling and Sampling Distributions 188 Chapter 8 Confidence Interval Estimation 225 Chapter 9 Fundamentals of Hypothesis Testing: One-Sample Tests 265 Chapter 10 Two-Sample Tests and One-Way ANOVA 300 Chapter 11 Chi-Square Tests 365 Chapter 12 Simple Linear Regression 393 Chapter 13 Multiple Regression 443 Chapter 14 Statistical Applications in Quality and Production Management 500 iii Preface The Test Item File contains a variety of multiple-choice, true-false, problem and fill-in questions based on the definitions, concepts, and ideas developed in each chapter. In addition, numerical problems and Microsoft Excel computer output problems are also given with solutions provided in multiple-choice, true-false, problem and fill-in format. The Test Item File is intended to assist instructors in preparing examinations. The questions included herein highlight the key topics covered throughout each chapter. Keywords are available after each question to help instructors locate questions on a specific topic or concept. Explanation is provided when the rationale of the correct answer to a difficult question is rather obscure. The format for the Test Item File will facilitate grading and should be helpful to instructors who teach very large sections. The intended difficulty level (easy, moderate, difficult) of each question in the Test Item File is stated in order to facilitate test item selection by instructors wishing to create specific types of exams. However, some words of caution must be given. The classification of question difficulty level is very subjective and each question should be evaluated based on the emphasis the particular topic was given in class and how much emphasis is to be given to numerical results obtained by calculator rather than computerized results obtained from Microsoft Excel. As an operational definition that is used here, items are classified as easy if they pertain directly to definitions and fundamental concepts. Test items are classified as moderate if they require some numerical calculations with more than a minimal number of steps or if they require a broader understanding of the topic. Test items that are classified as difficult are done so because of the level of rigor of the subject, the length of the narrative, the amount of effort required for solution, or for responses that require more thought and analysis. Instructors are also advised that all answers in the Test Item File are computed using Microsoft Excel or PHStat with no rounding involved in the intermediate steps. If students use rounding with formulae and a calculator, their answers might be different from those provided in the answer keys. Likewise, if students use the statistical tables at the end of the book instead of Microsoft Excel or PHStat, their answers might also differ from those provided in the answer keys due to rounding. Whenever possible, we provide answers obtained using both Microsoft Excel/PHStat and the statistical tables if they are different. This Test Item File and others that are similar suffer from one major weakness. They do not permit an evaluation of the students’ written communication skill. The authors highly recommend that, if possible, instructors who use this Test Item File supplement it with at least one short essay type question so that an assessment can be made of the students’ understanding of concepts as well as how they can make connections across various topics. The following tabular display is a breakdown of the number of questions in each chapter by type. iv Chapter Multiple Choice True/False Fill in Problem 1 48 42 40 0 130 2 51 32 83 18 184 3 27 33 31 38 129 4 60 19 38 37 154 5 21 13 47 41 122 6 16 14 43 48 121 7 44 65 39 31 179 8 29 105 27 21 182 9 70 57 16 7 150 10 109 51 57 53 270 11 45 31 31 6 113 12 78 33 59 28 198 13 102 51 42 18 213 14 44 24 35 10 113 Total 744 582 588 368 2282 v Total Keywords Index A a priori classical probability A2 factor addition rule adjusted coefficient of determination adjusted r-square assumption autocorrelation control limit convenience sample counting rule coverage error critical value cumulative frequency distribution cumulative percentage distribution cumulative percentage polygon (ogive) cumulative relative frequency B D bar chart Bayes' theorem beta-risk binomial distribution box-and-whisker plot d2 factor D3 factor D4 factor data decision degrees of freedom Deming's 14 points descriptive statistics deviance statistic difference between two means difference between two proportions difference between two variances discrete random variable dummy variable Durbin-Watson statistic C categorical random variable center line central limit theorem Chebyshev rule chi-square test Chi-square test for difference in proportions Chi-square test of independence chunk sample class boundaries class interval class midpoint cluster sample coefficient of correlation coefficient of determination coefficient of multiple determination coefficient of variation collective exhaustive column percentages combination common causes of variation complement completely randomized design conclusion conditional probability confidence coefficient confidence interval contingency table continuity adjustment continuous random variable control chart E empirical classical probability empirical rule estimation estimation of mean values ethical issues F F distribution F test F test for factor F test on slope F test on the entire regression fitted value five-number summary form of hypothesis frame frequency distribution vi H one-sided one-tailed test one-way analysis of variance ordinal scale outcomes histogram homoscedasticity I P inferential statistics interaction intercept interpretation interquartile range interval scale p chart Pareto diagram parameter percentage distribution percentage polygon permutation pie chart point estimate Poisson distribution polygon pooled variance population power prediction interval prediction of individual values primary data sources probability probability distribution probability sample properties proportion p-value J joint probability judgment sample L law of large number learning statistical programs least squares level of significance Levene's test M marginal probability mean (expected value) mean difference mean of the sum mean squares measure of variation measurement error measure of central tendency median mode multiplication rule mutually exclusive Q quadratic regression quartile quota sample R R chart random number range ratio scale reasons for learning statistics reasons for sampling red bead experiment rejection region relative frequency distribution residual residual plot resistant to outliers risk N nonprobability sample nonresponse error normal distribution normal probability plot number of classes O vii robust test row percentages two-tailed test type I error type II error types of data S U sample sample size sample size determination sample space sampling sampling distribution sampling error sampling method sampling with replacement sampling without replacement scatter plot secondary data sources selection bias shape Shewhart Deming cycle simple random sample six sigma management slope sources of data special causes of variation standard deviation standard error standard error of estimate standard normal quantile standardized normal distribution statistic statistical control statistical independence statistical package statistics stem-and-leaf display stratified sample subjective probability sum of squares survey worthiness systematic sample unbiased V value variance variance of sum variation W width X XBar chart Z Z scores Z test T t distribution t test t test for correlation coefficient t test on slope test statistic testing total percentages Tukey-Kramer procedure viii