Barbara Tabachnick is Professor Emerita of Psychology at California State University, Northridge, and co-author with Linda Fidell of Using Multivariate Statistics and Experimental Designs Using ANOVA. She has published over 70 articles and technical reports and participated in over 50 professional presentations, many invited. She currently presents workshops in computer applications in univariate and multivariate data analysis and consults in a variety of research areas, including professional ethics in and beyond academia, effects of such factors as age and substances on driving and performance, educational computer games, effects of noise on annoyance and sleep, and fetal alcohol syndrome. She is the recipient of the 2012 Western Psychological Association Lifetime Achievement Award.

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• In this Section:1. Brief Table of Contents2. Full Table of Contents  1. BRIEF TABLE OF CONTENTS  Chapter 1 IntroductionChapter 2 A Guide to Statistical Techniques: Using the BookChapter 3 Review of Univariate and Bivariate StatisticsChapter 4 Cleaning Up Your Act: Screening Data Prior to AnalysisChapter 5 Multiple RegressionChapter 6 Analysis of CovarianceChapter 7 Multivariate Analysis of Variance and CovarianceChapter 8 Profile Analysis: The Multivariate Approach to Repeated MeasuresChapter 9 Discriminant AnalysisChapter 10  Logistic RegressionChapter 11  Survival/Failure AnalysisChapter 12  Canonical CorrelationChapter 13  Principal Components and Factor AnalysisChapter 14  Structural Equation ModelingChapter 15  Multilevel Linear ModelingChapter 16  Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS  Chapter 1: IntroductionMultivariate Statistics: Why?Some Useful DefinitionsLinear Combinations of VariablesNumber and Nature of Variables to IncludeStatistical PowerData Appropriate for Multivariate StatisticsOrganization of the Book  Chapter 2: A Guide to Statistical Techniques: Using the BookResearch Questions and Associated TechniquesSome Further ComparisonsA Decision TreeTechnique ChaptersPreliminary Check of the Data  Chapter 3: Review of Univariate and Bivariate StatisticsHypothesis TestingAnalysis of VarianceParameter EstimationEffect SizeBivariate Statistics: Correlation and Regression.Chi-Square Analysis  Chapter 4: Cleaning Up Your Act: Screening Data Prior to AnalysisImportant Issues in Data ScreeningComplete Examples of Data Screening  Chapter 5: Multiple RegressionGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Regression AnalysesFundamental Equations for Multiple RegressionMajor Types of Multiple RegressionSome Important Issues.Complete Examples of Regression AnalysisComparison of Programs  Chapter 6: Analysis of CovarianceGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Analysis of CovarianceFundamental Equations for Analysis of CovarianceSome Important IssuesComplete Example of Analysis of CovarianceComparison of Programs  Chapter 7: Multivariate Analysis of Variance and CovarianceGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Multivariate Analysis of Variance and CovarianceFundamental Equations for Multivariate Analysis of Variance and CovarianceSome Important IssuesComplete Examples of Multivariate Analysis of Variance and CovarianceComparison of Programs  Chapter 8: Profile Analysis: The Multivariate Approach to Repeated MeasuresGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Profile AnalysisFundamental Equations for Profile AnalysisSome Important IssuesComplete Examples of Profile AnalysisComparison of Programs  Chapter 9: Discriminant AnalysisGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Discriminant AnalysisFundamental Equations for Discriminant AnalysisTypes of Discriminant AnalysisSome Important IssuesComparison of Programs  Chapter 10: Logistic Regres

Barbara Tabachnick is Professor Emerita of Psychology at California State University, Northridge, and co-author with Linda Fidell of Using Multivariate Statistics and Experimental Designs Using ANOVA. She has published over 70 articles and technical reports and participated in over 50 professional presentations, many invited. She currently presents workshops in computer applications in univariate and multivariate data analysis and consults in a variety of research areas, including professional ethics in and beyond academia, effects of such factors as age and substances on driving and performance, educational computer games, effects of noise on annoyance and sleep, and fetal alcohol syndrome. She is the recipient of the 2012 Western Psychological Association Lifetime Achievement Award.

Select Guide Rating

• In this Section:1. Brief Table of Contents2. Full Table of Contents  1. BRIEF TABLE OF CONTENTS  Chapter 1 IntroductionChapter 2 A Guide to Statistical Techniques: Using the BookChapter 3 Review of Univariate and Bivariate StatisticsChapter 4 Cleaning Up Your Act: Screening Data Prior to AnalysisChapter 5 Multiple RegressionChapter 6 Analysis of CovarianceChapter 7 Multivariate Analysis of Variance and CovarianceChapter 8 Profile Analysis: The Multivariate Approach to Repeated MeasuresChapter 9 Discriminant AnalysisChapter 10  Logistic RegressionChapter 11  Survival/Failure AnalysisChapter 12  Canonical CorrelationChapter 13  Principal Components and Factor AnalysisChapter 14  Structural Equation ModelingChapter 15  Multilevel Linear ModelingChapter 16  Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS  Chapter 1: IntroductionMultivariate Statistics: Why?Some Useful DefinitionsLinear Combinations of VariablesNumber and Nature of Variables to IncludeStatistical PowerData Appropriate for Multivariate StatisticsOrganization of the Book  Chapter 2: A Guide to Statistical Techniques: Using the BookResearch Questions and Associated TechniquesSome Further ComparisonsA Decision TreeTechnique ChaptersPreliminary Check of the Data  Chapter 3: Review of Univariate and Bivariate StatisticsHypothesis TestingAnalysis of VarianceParameter EstimationEffect SizeBivariate Statistics: Correlation and Regression.Chi-Square Analysis  Chapter 4: Cleaning Up Your Act: Screening Data Prior to AnalysisImportant Issues in Data ScreeningComplete Examples of Data Screening  Chapter 5: Multiple RegressionGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Regression AnalysesFundamental Equations for Multiple RegressionMajor Types of Multiple RegressionSome Important Issues.Complete Examples of Regression AnalysisComparison of Programs  Chapter 6: Analysis of CovarianceGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Analysis of CovarianceFundamental Equations for Analysis of CovarianceSome Important IssuesComplete Example of Analysis of CovarianceComparison of Programs  Chapter 7: Multivariate Analysis of Variance and CovarianceGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Multivariate Analysis of Variance and CovarianceFundamental Equations for Multivariate Analysis of Variance and CovarianceSome Important IssuesComplete Examples of Multivariate Analysis of Variance and CovarianceComparison of Programs  Chapter 8: Profile Analysis: The Multivariate Approach to Repeated MeasuresGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Profile AnalysisFundamental Equations for Profile AnalysisSome Important IssuesComplete Examples of Profile AnalysisComparison of Programs  Chapter 9: Discriminant AnalysisGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Discriminant AnalysisFundamental Equations for Discriminant AnalysisTypes of Discriminant AnalysisSome Important IssuesComparison of Programs  Chapter 10: Logistic Regres

Barbara Tabachnick is Professor Emerita of Psychology at California State University, Northridge, and co-author with Linda Fidell of Using Multivariate Statistics and Experimental Designs Using ANOVA. She has published over 70 articles and technical reports and participated in over 50 professional presentations, many invited. She currently presents workshops in computer applications in univariate and multivariate data analysis and consults in a variety of research areas, including professional ethics in and beyond academia, effects of such factors as age and substances on driving and performance, educational computer games, effects of noise on annoyance and sleep, and fetal alcohol syndrome. She is the recipient of the 2012 Western Psychological Association Lifetime Achievement Award.

Select Guide Rating

• In this Section:1. Brief Table of Contents2. Full Table of Contents  1. BRIEF TABLE OF CONTENTS  Chapter 1 IntroductionChapter 2 A Guide to Statistical Techniques: Using the BookChapter 3 Review of Univariate and Bivariate StatisticsChapter 4 Cleaning Up Your Act: Screening Data Prior to AnalysisChapter 5 Multiple RegressionChapter 6 Analysis of CovarianceChapter 7 Multivariate Analysis of Variance and CovarianceChapter 8 Profile Analysis: The Multivariate Approach to Repeated MeasuresChapter 9 Discriminant AnalysisChapter 10  Logistic RegressionChapter 11  Survival/Failure AnalysisChapter 12  Canonical CorrelationChapter 13  Principal Components and Factor AnalysisChapter 14  Structural Equation ModelingChapter 15  Multilevel Linear ModelingChapter 16  Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS  Chapter 1: IntroductionMultivariate Statistics: Why?Some Useful DefinitionsLinear Combinations of VariablesNumber and Nature of Variables to IncludeStatistical PowerData Appropriate for Multivariate StatisticsOrganization of the Book  Chapter 2: A Guide to Statistical Techniques: Using the BookResearch Questions and Associated TechniquesSome Further ComparisonsA Decision TreeTechnique ChaptersPreliminary Check of the Data  Chapter 3: Review of Univariate and Bivariate StatisticsHypothesis TestingAnalysis of VarianceParameter EstimationEffect SizeBivariate Statistics: Correlation and Regression.Chi-Square Analysis  Chapter 4: Cleaning Up Your Act: Screening Data Prior to AnalysisImportant Issues in Data ScreeningComplete Examples of Data Screening  Chapter 5: Multiple RegressionGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Regression AnalysesFundamental Equations for Multiple RegressionMajor Types of Multiple RegressionSome Important Issues.Complete Examples of Regression AnalysisComparison of Programs  Chapter 6: Analysis of CovarianceGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Analysis of CovarianceFundamental Equations for Analysis of CovarianceSome Important IssuesComplete Example of Analysis of CovarianceComparison of Programs  Chapter 7: Multivariate Analysis of Variance and CovarianceGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Multivariate Analysis of Variance and CovarianceFundamental Equations for Multivariate Analysis of Variance and CovarianceSome Important IssuesComplete Examples of Multivariate Analysis of Variance and CovarianceComparison of Programs  Chapter 8: Profile Analysis: The Multivariate Approach to Repeated MeasuresGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Profile AnalysisFundamental Equations for Profile AnalysisSome Important IssuesComplete Examples of Profile AnalysisComparison of Programs  Chapter 9: Discriminant AnalysisGeneral Purpose and DescriptionKinds of Research QuestionsLimitations to Discriminant AnalysisFundamental Equations for Discriminant AnalysisTypes of Discriminant AnalysisSome Important IssuesComparison of Programs  Chapter 10: Logistic Regres