Performing Data Analysis Using IBM SPSS

Performing Data Analysis Using IBM SPSS

By: Glenn C. Gamst (author), Lawrence S. Meyers (author), A. J. Guarino (author)Paperback

1 - 2 weeks availability

£62.05 RRP £68.95  You save £6.90 (10%) With FREE Saver Delivery

Description

Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS(R) Performing Data Analysis Using IBM SPSS(R) 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.

Create a review

About 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.

Contents

PREFACE ix PART 1 GETTING STARTED WITH IBM SPSS(R) 1 CHAPTER 1 INTRODUCTION TO IBM SPSS(R) 3 CHAPTER 2 ENTERING DATA IN IBM SPSS(R) 5 CHAPTER 3 IMPORTING DATA FROM EXCEL TO IBM SPSS(R) 15 PART 2 OBTAINING, EDITING, AND SAVING STATISTICAL OUTPUT 19 CHAPTER 4 PERFORMING STATISTICAL PROCEDURES IN IBM SPSS(R) 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

Product Details

  • publication date: 27/09/2013
  • ISBN13: 9781118357019
  • Format: Paperback
  • Number Of Pages: 736
  • ID: 9781118357019
  • weight: 1774
  • ISBN10: 1118357019

Delivery Information

  • Saver Delivery: Yes
  • 1st Class Delivery: Yes
  • Courier Delivery: Yes
  • Store Delivery: Yes

Prices are for internet purchases only. Prices and availability in WHSmith Stores may vary significantly

Close