Performing Data Analysis Using IBM SPSS [NOOK Book]

Overview

Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS®

Performing Data Analysis Using IBM SPSS® uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and-click methods, including details on how to view and ...

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Performing Data Analysis Using IBM SPSS

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Overview

Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS®

Performing Data Analysis Using IBM SPSS® uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and-click methods, including details on how to view and manipulate output.

Designed as a user's guide for students and other interested readers to perform statistical data analysis with IBM SPSS, this book addresses the needs, level of sophistication, and interest in introductory statistical methodology on the part of readers in social and behavioral science, business, health-related, and education programs. Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis.

The book provides in-depth chapter coverage of:

  • IBM SPSS statistical output
  • Descriptive statistics procedures
  • Score distribution assumption evaluations
  • Bivariate correlation
  • Regressing (predicting) quantitative and categorical variables
  • Survival analysis
  • t Test
  • ANOVA and ANCOVA
  • Multivariate group differences
  • Multidimensional scaling
  • Cluster analysis
  • Nonparametric procedures for frequency data

Performing Data Analysis Using IBM SPSS is an excellent text for upper-undergraduate and graduate-level students in courses on social, behavioral, and health sciences as well as secondary education, research design, and statistics. Also an excellent reference, the book is ideal for professionals and researchers in the social, behavioral, and health sciences; applied statisticians; and practitioners working in industry.

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Product Details

  • ISBN-13: 9781118363577
  • Publisher: Wiley
  • Publication date: 7/17/2013
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • Pages: 736
  • Sales rank: 743,038
  • File size: 106 MB
  • Note: This product may take a few minutes to download.

Meet the Author

LAWRENCE S. MEYERS, PhD, is Professor in the Depart-ment of Psychology at California State University, Sacramento. The author of numerous books, Dr. Meyers is a member of the Association for Psychological Science and the Society for Industrial and Organiza-tional Psychology.

GLENN C. GAMST, PhD, is Chair and Professor in the Department of Psychology at the University of La Verne. His research interests include univariate and multivariate statistics as well as multicultural community mental health outcome research.

A. J. Guarino, PhD, is Professor of Biostatistics at Massachusetts General Hospital, Institute of Health Professions, where he serves as the methodologist for capstones and dissertations as well as teaching advanced Biostatistics courses. Dr. Guarino is also the statistician on numerous National Institutes of Health grants and coauthor of several statistical textbooks.

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Table of Contents

PREFACE ix

PART 1  GETTING STARTED WITH IBM SPSS® 1

CHAPTER 1  INTRODUCTION TO IBM SPSS® 3

CHAPTER 2  ENTERING DATA IN IBM SPSS® 5

CHAPTER 3  IMPORTING DATA FROM EXCEL TO IBM SPSS® 15

PART 2  OBTAINING, EDITING, AND SAVING STATISTICAL OUTPUT 19

CHAPTER 4  PERFORMING STATISTICAL PROCEDURES IN IBM SPSS® 21

CHAPTER 5  EDITING OUTPUT 27

CHAPTER 6  SAVING AND COPYING OUTPUT 31

PART 3  MANIPULATING DATA 37

CHAPTER 7  SORTING AND SELECTING CASES 39

CHAPTER 8  SPLITTING DATA FILES 45

CHAPTER 9  MERGING DATA FROM SEPARATE FILES 51

PART 4  DESCRIPTIVE STATISTICS PROCEDURES 57

CHAPTER 10  FREQUENCIES 59

CHAPTER 11  DESCRIPTIVES 67

CHAPTER 12  EXPLORE 71

PART 5  SIMPLE DATA TRANSFORMATIONS 77

CHAPTER 13  STANDARDIZING VARIABLES TO Z SCORES 79

CHAPTER 14  RECODING VARIABLES 83

CHAPTER 15  VISUAL BINNING 97

CHAPTER 16  COMPUTING NEW VARIABLES 103

CHAPTER 17  TRANSFORMING DATES TO AGE 111

PART 6  EVALUATING SCORE DISTRIBUTION ASSUMPTIONS 121

CHAPTER 18  DETECTING UNIVARIATE OUTLIERS 123

CHAPTER 19  DETECTING MULTIVARIATE OUTLIERS 131

CHAPTER 20  ASSESSING DISTRIBUTION SHAPE: NORMALITY, SKEWNESS, AND KURTOSIS 139

CHAPTER 21  TRANSFORMING DATA TO REMEDY STATISTICAL ASSUMPTION VIOLATIONS 147

PART 7  BIVARIATE CORRELATION 157

CHAPTER 22  PEARSON CORRELATION 159

CHAPTER 23  SPEARMAN RHO AND KENDALL TAU-B RANK-ORDER CORRELATIONS 165

PART 8  REGRESSING (PREDICTING) QUANTITATIVE VARIABLES 171

CHAPTER 24  SIMPLE LINEAR REGRESSION 173

CHAPTER 25  CENTERING THE PREDICTOR VARIABLE IN SIMPLE LINEAR REGRESSION 181

CHAPTER 26  MULTIPLE LINEAR REGRESSION 191

CHAPTER 27  HIERARCHICAL LINEAR REGRESSION 211

CHAPTER 28  POLYNOMIAL REGRESSION 217

CHAPTER 29  MULTILEVEL MODELING 225

PART 9  REGRESSING (PREDICTING) CATEGORICAL VARIABLES 253

CHAPTER 30  BINARY LOGISTIC REGRESSION 255

CHAPTER 31  ROC ANALYSIS 265

CHAPTER 32  MULTINOMINAL LOGISTIC REGRESSION 273

PART 10  SURVIVAL ANALYSIS 281

CHAPTER 33  SURVIVAL ANALYSIS: LIFE TABLES 283

CHAPTER 34  THE KAPLAN–MEIER SURVIVAL ANALYSIS 289

CHAPTER 35  COX REGRESSION 301

PART 11  RELIABILITY AS A GAUGE OF MEASUREMENT QUALITY 309

CHAPTER 36  RELIABILITY ANALYSIS: INTERNAL CONSISTENCY 311

CHAPTER 37  RELIABILITY ANALYSIS: ASSESSING RATER CONSISTENCY 319

PART 12  ANALYSIS OF STRUCTURE 329

CHAPTER 38  PRINCIPAL COMPONENTS AND FACTOR ANALYSIS 331

CHAPTER 39  CONFIRMATORY FACTOR ANALYSIS 353

PART 13  EVALUATING CAUSAL (PREDICTIVE) MODELS 379

CHAPTER 40  SIMPLE MEDIATION 381

CHAPTER 41  PATH ANALYSIS USING MULTIPLE REGRESSION 389

CHAPTER 42  PATH ANALYSIS USING STRUCTURAL EQUATION MODELING 397

CHAPTER 43  STRUCTURAL EQUATION MODELING 419

PART 14  t TEST 457

CHAPTER 44  ONE-SAMPLE t TEST 459

CHAPTER 45  INDEPENDENT-SAMPLES t TEST 463

CHAPTER 46  PAIRED-SAMPLES t TEST 471

PART 15  UNIVARIATE GROUP DIFFERENCES: ANOVA AND ANCOVA 475

CHAPTER 47  ONE-WAY BETWEEN-SUBJECTS ANOVA 477

CHAPTER 48  POLYNOMIAL TREND ANALYSIS 485

CHAPTER 49  ONE-WAY BETWEEN-SUBJECTS ANCOVA 493

CHAPTER 50  TWO-WAY BETWEEN-SUBJECTS ANOVA 507

CHAPTER 51  ONE-WAY WITHIN-SUBJECTS ANOVA 521

CHAPTER 52  REPEATED MEASURES USING LINEAR MIXED MODELS 531

CHAPTER 53  TWO-WAY MIXED ANOVA 555

PART 16  MULTIVARIATE GROUP DIFFERENCES: MANOVA AND DISCRIMINANT FUNCTION ANALYSIS 567

CHAPTER 54  ONE-WAY BETWEEN-SUBJECTS MANOVA 569

CHAPTER 55  DISCRIMINANT FUNCTION ANALYSIS 579

CHAPTER 56  TWO-WAY BETWEEN-SUBJECTS MANOVA 591

PART 17  MULTIDIMENSIONAL SCALING 603

CHAPTER 57  MULTIDIMENSIONAL SCALING: CLASSICAL METRIC 605

CHAPTER 58  MULTIDIMENSIONAL SCALING: METRIC WEIGHTED 613

PART 18  CLUSTER ANALYSIS 621

CHAPTER 59  HIERARCHICAL CLUSTER ANALYSIS 623

CHAPTER 60  K-MEANS CLUSTER ANALYSIS 631

PART 19  NONPARAMETRIC PROCEDURES FOR ANALYZING FREQUENCY DATA 643

CHAPTER 61  SINGLE-SAMPLE BINOMIAL AND CHI-SQUARE TESTS: BINARY CATEGORIES 645

CHAPTER 62  SINGLE-SAMPLE (ONE-WAY) MULTINOMINAL CHI-SQUARE TESTS 655

CHAPTER 63  TWO-WAY CHI-SQUARE TEST OF INDEPENDENCE 665

CHAPTER 64  RISK ANALYSIS 675

CHAPTER 65  CHI-SQUARE LAYERS 681

CHAPTER 66  HIERARCHICAL LOGLINEAR ANALYSIS 689

APPENDIX  STATISTICS TABLES 699

REFERENCES 703

AUTHOR INDEX 713

SUBJECT INDEX 715

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  • Anonymous

    Posted January 29, 2014

    Great book! I used this and The 7 Steps of Data Analysis (Bannon

    Great book! I used this and The 7 Steps of Data Analysis (Bannon) to get through my coursework!

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