Statistics SPSS data

Humanities

Asheville Buncombe Technical Community College

Question Description

Follow instructions from Doing Data Analysis with SPSS, Session 12 and practice

• Working with Two Samples
• Paired versus Independent Samples
Please replicate the exercises and answer the questions the book presented, based on your analysis of the output.
Please include the output, result analysis, and answers for the questions in your assignment.


SESSION IS FINISHED ONCE YOU REACHED MOVING ON...

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Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Doing Data Analysis with SPSS® Version 18 Robert H. Carver Stonehill College Jane Gradwohl Nash Stonehill College Australia • Brazil • Japan • Korea • Mexico • Singapore • Spain • United Kingdom • United States Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Doing Data Analysis with SPSS® Version 18 Robert H. Carver, Jane Gradwohl Nash Publisher: Richard Stratton Senior Sponsoring Editor: Molly Taylor Assistant Editor: Shaylin Walsh © 2012, 2009, 2006, Brooks/Cole Cengage Learning ALL RIGHTS RESERVED. No part of this work covered by the copyright herein may be reproduced, transmitted, stored or used in any form or by any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, information networks, or information storage and retrieval systems, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the publisher. Media Editor: Andrew Coppola Marketing Manager: Jennifer Jones Marketing Coordinator: Michael Ledesma Marketing Communications Manager: Mary Anne Payumo Content Project Management: PreMediaGlobal Art Director: Linda Helcher Print Buyer: Diane Gibbons Production Service: PreMediaGlobal Cover Designer: Rokusek Design Cover Image: Kostyantyn Ivanyshen/ ©Shutterstock Compositor: PreMediaGlobal For permission to use material from this text or product, submit all requests online at www.cengage.com/permissions Further permissions questions can be e-mailed to permissionrequest@cengage.com Library of Congress Control Number: 2010942243 Student Edition: ISBN-13: 978-0-8400-4916-2 ISBN-10: 0-8400-4916-1 Cengage Learning 20 Channel Center Street Boston, MA 02210 USA Represented in Canada by Nelson Education, Ltd. tel: (416) 752 9100 / (800) 668 0671 www.nelson.com Cengage Learning is a leading provider of customized learning solutions with office locations around the globe, including Singapore, the United Kingdom, Australia, Mexico, Brazil and Japan. Locate your local office at international.cengage.com/region Cengage Learning products are represented in Canada by Nelson Education, Ltd. For your course and learning solutions, visit www.cengage.com. Purchase any of our products at your local college store or at our preferred online store www.cengagebrain.com. Instructors: Please visit login.cengage.com and log in to access instructor-specific resources. Printed in the United States 1 2 3 4 5 6 7 15 14 13 12 11 Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. In loving memory of my brother and teacher Barry, and for Donna, Sam, and Ben, who teach me daily. RHC For Justin, Hanna and Sara—you are my world. JGN Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Contents Session 1. A First Look at SPSS Statisitcs 18 1 Objectives 1 Launching SPSS/PASW Statistics 18 1 Entering Data into the Data Editor 3 Saving a Data File 6 Creating a Bar Chart 7 Saving an Output File 11 Getting Help 12 Printing in SPSS 12 Quitting SPSS 12 Session 2. Tables and Graphs for One Variable 13 Objectives 13 Opening a Data File 13 Exploring the Data 14 Creating a Histogram 16 Frequency Distributions 20 Another Bar Chart 22 Printing Session Output 22 Moving On… 23 Session 3. Tables and Graphs for Two Variables 27 Objectives 27 Cross-Tabulating Data 27 Editing a Recent Dialog 29 More on Bar Charts 29 Comparing Two Distributions 32 v Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. vi Contents Scatterplots to Detect Relationships 33 Moving On… 34 Session 4. One-Variable Descriptive Statistics 39 Objectives 39 Computing One Summary Measure for a Variable 39 Computing Additional Summary Measures 43 A Box-and-Whiskers Plot 46 Standardizing a Variable 47 Moving On… 48 Session 5. Two-Variable Descriptive Statistics 51 Objectives 51 Comparing Dispersion with the Coefficient of Variation 51 Descriptive Measures for Subsamples 53 Measures of Association: Covariance and Correlation 54 Moving On… 57 Session 6. Elementary Probability 61 Objectives 61 Simulation 61 A Classical Example 61 Observed Relative Frequency as Probability 63 Handling Alphanumeric Data 65 Moving On… 68 Session 7. Discrete Probability Distributions 71 Objectives 71 An Empirical Discrete Distribution 71 Graphing a Distribution 73 A Theoretical Distribution: The Binomial 74 Another Theoretical Distribution: The Poisson 76 Moving On… 77 Session 8. Normal Density Functions 81 Objectives 81 Continuous Random Variables 81 Generating Normal Distributions 82 Finding Areas under a Normal Curve 85 Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Contents vii Normal Curves as Models 87 Moving On... 89 Session 9. Sampling Distributions 93 Objectives 93 What Is a Sampling Distribution? 93 Sampling from a Normal Population 94 Central Limit Theorem 97 Sampling Distribution of the Proportion 99 Moving On... 100 Session 10. Confidence Intervals 103 Objectives 103 The Concept of a Confidence Interval 103 Effect of Confidence Coefficient 106 Large Samples from a Non-normal (Known) Population 106 Dealing with Real Data 107 Small Samples from a Normal Population 108 Moving On... 110 Session 11. One-Sample Hypothesis Tests 113 Objectives 113 The Logic of Hypothesis Testing 113 An Artificial Example 114 A More Realistic Case: We Don't Know Mu or Sigma 117 A Small-Sample Example 119 Moving On... 121 Session 12. Two-Sample Hypothesis Tests 125 Objectives 125 Working with Two Samples 125 Paired vs. Independent Samples 130 Moving On... 132 Session 13. Analysis of Variance (I) 137 Objectives 137 Comparing Three or More Means 137 One-Factor Independent Measures ANOVA 138 Where Are the Differences? 142 Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. viii Contents One-Factor Repeated Measures ANOVA 144 Where Are the Differences? 149 Moving On… 149 Session 14. Analysis of Variance (II) 153 Objectives 153 Two-Factor Independent Measures ANOVA 153 Another Example 159 One Last Note 161 Moving On… 162 Session 15. Linear Regression (I) 165 Objectives 165 Linear Relationships 165 Another Example 170 Statistical Inferences in Linear Regression 171 An Example of a Questionable Relationship 172 An Estimation Application 173 A Classic Example 174 Moving On... 175 Session 16. Linear Regression (II) 179 Objectives 179 Assumptions for Least Squares Regression 179 Examining Residuals to Check Assumptions 180 A Time Series Example 185 Issues in Forecasting and Prediction 187 A Caveat about "Mindless" Regression 190 Moving On... 191 Session 17. Multiple Regression 195 Objectives 195 Going Beyond a Single Explanatory Variable 195 Significance Testing and Goodness of Fit 201 Residual Analysis 202 Adding More Variables 202 Another Example 203 Working with Qualitative Variables 204 A New Concern 206 Moving On… 207 Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Contents ix Session 18. Nonlinear Models 211 Objectives 211 When Relationships Are Not Linear 211 A Simple Example 212 Some Common Transformations 213 Another Quadratic Model 215 A Log-Linear Model 220 Adding More Variables 221 Moving On… 221 Session 19. Basic Forecasting Techniques 225 Objectives 225 Detecting Patterns over Time 225 Some Illustrative Examples 226 Forecasting Using Moving Averages 228 Forecasting Using Trend Analysis 231 Another Example 234 Moving On… 234 Session 20. Chi-Square Tests 237 Objectives 237 Qualitative vs. Quantitative Data 237 Chi-Square Goodness-of-Fit Test 237 Chi-Square Test of Independence 241 Another Example 244 Moving On... 245 Session 21. Nonparametric Tests 249 Objectives 249 Nonparametric Methods 249 Mann-Whitney U Test 250 Wilcoxon Signed Ranks Test 252 Kruskal-Wallis H Test 254 Spearman’s Rank Order Correlation 257 Moving On… 258 Session 22. Tools for Quality 261 Objectives 261 Processes and Variation 261 Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. x Contents Charting a Process Mean 262 Charting a Process Range 265 Another Way to Organize Data 266 Charting a Process Proportion 268 Pareto Charts 270 Moving On… 272 Appendix A. Dataset Descriptions 275 Appendix B. Working with Files 309 Objectives 309 Data Files 309 Viewer Document Files 310 Converting Other Data Files into SPSS Data Files 311 Index 315 Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Preface Quantitative Reasoning, Real Data, and Active Learning Most undergraduate students in the U.S. now take an introductory course in statistics, and many of us who teach statistics strive to engage students in the practice of data analysis and quantitative thinking about real problems. With the widespread availability of personal computers and statistical software, and the near-universal application of quantitative methods in many professions, introductory statistics courses now emphasize statistical reasoning more than computational skill development. Questions of how have given way to more challenging questions of why, when, and what? The goal of this book is to supplement an introductory undergraduate statistics course with a comprehensive set of self-paced exercises. Students can work independently, learning the software skills outside of class, while coming to understand the underlying statistical concepts and techniques. Instructors can teach statistics and statistical reasoning, rather than teaching algebra or software. Both students and teachers can devote their energies to using data analysis in ways that inform their understanding of the world and investigate problems that really matter. The Approach of This Book The book reflects the changes described above in several ways. First and most obviously it provides some training in the use of a powerful software package to relieve students of computational drudgery. Second, each session is designed to address a statistical issue or need, rather than to feature a particular command or menu in the software. xi Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. xii Preface Third, nearly all of the datasets in the book are real, reflecting a variety of disciplines and underscoring the wide applicability of statistical reasoning. Fourth, the sessions follow a traditional sequence, making the book compatible with many texts. Finally, as each session leads students through the techniques, it also includes thought-provoking questions and challenges, engaging the student in the processes of statistical reasoning. In designing the sessions, we kept four ideas in mind: • Statistical reasoning, not computation, is the goal of the course. This book asks students questions throughout, balancing software instruction with reflection on the meaning of results. • Students arrive in the course ready to engage in statistical reasoning. They need not slog all the way through descriptive techniques before encountering the concept of inference. The exercises invite students to think about inferences from the start, and the questions grow in sophistication as students master new material. • Exploration of real data is preferable to artificial datasets. With the exception of the famous Anscombe regression dataset and a few simulations, all of the datasets are real. Some are very old and some are quite current, and they cover a wide range of substantive areas. • Statistical topics, rather than software features, should drive the design of each session. Each session features several SPSS functions selected for their relevance to the statistical concept under consideration. This book provides a rigorous but limited introduction to the software produced by SPSS, an IBM company.1 The SPSS/PASW2 Statistics 18 system is rich in features and options; this book makes no attempt to “cover” the entire package. Instead, the level of coverage is commensurate with an introductory course. There may be many ways to perform a given task in SPSS; generally, we show one way. This book provides a “foot in the door.” Interested students and other users can explore the software possibilities via the extensive Help system or other standard SPSS documentation. SPSS was acquired by IBM in October 2009. SPSS Statistics 18 was formerly known as PASW Statistics 18, and the PASW name appears on several screens in the software. The book will reference the SPSS name only, but note that SPSS and PASW are interchangeable terms. 1 2 Copyright 2010 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. Preface xiii Using This Book We presume that this book is being used as a supplementary text in an introductory-level statistics course. If your courses are like ours (one in a psychology department, the other in a business department), class time is a scarce resource. Adding new material is always a balancing act. As such, supplementary readings and assignments must be carefully integrated. We suggest that instructors use the sessions in this book in four different ways, tailoring the approach throughout the term to meet the needs of the students and course. • • • • In-class activity: Part or all of some sessions might best be done together in class, with each student at a computer. The instructor can comment on particular points and can roam to offer assistance. This may be especially effective in the earliest sessions. Stand-alone assignments: In conjunction with a topic covered in the principal text, sessions can be assigned as independent out-of-class work, along with selected Moving On… questions. This is our most frequently-used approach. Students independently learn the software, re-enforce the statistical concepts, and come to class with questions about any difficulties they encountered in the lab session. Preparation for text-based case or problem: An instructor may wish to use a textbook case for a major assignment. The relevant session may prepare the class with the software skills needed to complete the case. Independent projects: Sessions may be assigned to prepare students to undertake an independent analysis project designed by the instructor. Many of the data files provided with the book contain additional variables that are never used within sessions. These variables may form the basis for original analyses or explorations. Solutions are available to instructors for all Moving On… and bold-faced questions. Instructors should consult their Cengage Learning sales representatives for details. A companion website is available to both instructors and students at www.cengage.com/statistics/carver. The Data Files As previously no ...
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