Description

Book Synopsis
An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to analyze multivariate data. The book focuses on the statistics generally covered in an intermediate or multivariate statistics course and provides one or two ways to run each analysis in R. The book has been designed to be an R companion to Rebecca M. Warner's Applied Statistics II: Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide for a multivariate statistics course, without reference to the Warner text. Datasets and scripts to run the examples are provided on an accompanying website.


Table of Contents
Preface Acknowledgments About the Author CHAPTER 1 • Beyond Two Variables and Null Hypothesis Significance Testing Confidence Intervals Effect Size Meta-Analysis Chapter 1: Summary of Key Functions (AKA: Function Cheat Sheet) CHAPTER 2 • Advanced Data Screening, Outliers, and Missing Values Data Management Coding Missing Values Screening Data Chapter 2: Summary of Key Functions (AKA: Function Cheat Sheet) CHAPTER 3 • Statistical Control Including a Third Variable in Graphs Including a Third Variable Quantitatively Chapter 3: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 3: R Instructions to Accompany Warner (2020b) CHAPTER 4 • Statistical Control With Regression Analysis Visualizing Associations Between Three Variables Performing Regressions and Semipartial Correlations Chapter 4: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 4: R Instructions to Accompany Warner (2020b) CHAPTER 5 • Beyond Three Variables: Regression With Multiple Predictors Standard Regression User-Determined Regression Data-Driven Regression Chapter 5: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 5: R Instructions to Accompany Warner (2020b) CHAPTER 6 • Regression With Dummy Variables One-Way Between-Subjects Analysis of Variance (ANOVA) Regression With Dummy Variables Regression With Quantitative and Dummy Variables Chapter 6: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 6: R Instructions to Accompany Warner (2020b) CHAPTER 7 • Moderation Interactions With Categorical Predictors Interactions With a Categorical and Quantitative Predictor Interactions With Two Quantitative Predictors Interactions with a Categorical and Quantitative Predictor Interactions with Two Quantitative Predictors Chapter 7: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 7: R Instructions to Accompany Warner (2020b) CHAPTER 8 • Analysis of Covariance Checking Assumptions Performing ANCOVA Presenting Results Chapter 8: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 8: R Instructions to Accompany Warner (2020b) CHAPTER 9 • Mediation Checking Assumptions Performing Mediation Analysis Presenting Results Chapter 9: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 9: R Instructions to Accompany Warner (2020b) CHAPTER 10 • Discriminant Analysis Checking Assumptions Performing Discriminant Analysis Presenting Results Chapter 10: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 10: R Instructions to Accompany Warner (2020b) CHAPTER 11 • Multivariate Analysis of Variance Checking Assumptions Performing Multivariate Analysis of Variance Performing Factorial Multivariate Analysis of Variance Chapter 11: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 11: R Instructions to Accompany Warner (2020b) CHAPTER 12 • Exploratory Factor Analysis Performing Principal Components Analysis Performing Principal Axis Factor Analysis Chapter 12: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 12: R Instructions to Accompany Warner (2020b) CHAPTER 13 • Reliability and Validity for Multiple-Item Scales Test-Retest Reliability Factor Analysis Internal Reliability and Creating Scale Scores Chapter 13: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 13: R Instructions to Accompany Warner (2020b) CHAPTER 14 • Repeated-Measures Tests: Further Exploration Checking Assumptions One-Way Repeated-Measures Analysis of Variance Mixed Analysis of Variance Chapter 14: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 14: R Instructions to Accompany Warner (2020b) CHAPTER 15 • Brief Introduction to Latent-Variable Structural Equation Modeling Measurement Models Mediation With Latent-Variable Structural Equation Modeling Chapter 15: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 15: R Instructions to Accompany Warner (2020b) CHAPTER 16 • Binary Logistic Regression Getting Familiar With the Data Binary Logistic Regression Presenting Results Chapter 16: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 16: R Instructions to Accompany Warner (2020b) CHAPTER 17 • Additional Statistical Techniques Dealing With Time Dealing With Odd Distributions Dealing With Interdependence Concluding Thoughts References

An R Companion for Applied Statistics II

    Product form

    £54.00

    Includes FREE delivery

    Order before 4pm today for delivery by Wed 17 Jun 2026.

    1 in stock

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of An R Companion for Applied Statistics II by

      Publisher:
      Publication Date:
      ISBN13: ,
      ISBN10:

      Description

      Book Synopsis
      An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to analyze multivariate data. The book focuses on the statistics generally covered in an intermediate or multivariate statistics course and provides one or two ways to run each analysis in R. The book has been designed to be an R companion to Rebecca M. Warner's Applied Statistics II: Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide for a multivariate statistics course, without reference to the Warner text. Datasets and scripts to run the examples are provided on an accompanying website.


      Table of Contents
      Preface Acknowledgments About the Author CHAPTER 1 • Beyond Two Variables and Null Hypothesis Significance Testing Confidence Intervals Effect Size Meta-Analysis Chapter 1: Summary of Key Functions (AKA: Function Cheat Sheet) CHAPTER 2 • Advanced Data Screening, Outliers, and Missing Values Data Management Coding Missing Values Screening Data Chapter 2: Summary of Key Functions (AKA: Function Cheat Sheet) CHAPTER 3 • Statistical Control Including a Third Variable in Graphs Including a Third Variable Quantitatively Chapter 3: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 3: R Instructions to Accompany Warner (2020b) CHAPTER 4 • Statistical Control With Regression Analysis Visualizing Associations Between Three Variables Performing Regressions and Semipartial Correlations Chapter 4: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 4: R Instructions to Accompany Warner (2020b) CHAPTER 5 • Beyond Three Variables: Regression With Multiple Predictors Standard Regression User-Determined Regression Data-Driven Regression Chapter 5: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 5: R Instructions to Accompany Warner (2020b) CHAPTER 6 • Regression With Dummy Variables One-Way Between-Subjects Analysis of Variance (ANOVA) Regression With Dummy Variables Regression With Quantitative and Dummy Variables Chapter 6: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 6: R Instructions to Accompany Warner (2020b) CHAPTER 7 • Moderation Interactions With Categorical Predictors Interactions With a Categorical and Quantitative Predictor Interactions With Two Quantitative Predictors Interactions with a Categorical and Quantitative Predictor Interactions with Two Quantitative Predictors Chapter 7: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 7: R Instructions to Accompany Warner (2020b) CHAPTER 8 • Analysis of Covariance Checking Assumptions Performing ANCOVA Presenting Results Chapter 8: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 8: R Instructions to Accompany Warner (2020b) CHAPTER 9 • Mediation Checking Assumptions Performing Mediation Analysis Presenting Results Chapter 9: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 9: R Instructions to Accompany Warner (2020b) CHAPTER 10 • Discriminant Analysis Checking Assumptions Performing Discriminant Analysis Presenting Results Chapter 10: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 10: R Instructions to Accompany Warner (2020b) CHAPTER 11 • Multivariate Analysis of Variance Checking Assumptions Performing Multivariate Analysis of Variance Performing Factorial Multivariate Analysis of Variance Chapter 11: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 11: R Instructions to Accompany Warner (2020b) CHAPTER 12 • Exploratory Factor Analysis Performing Principal Components Analysis Performing Principal Axis Factor Analysis Chapter 12: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 12: R Instructions to Accompany Warner (2020b) CHAPTER 13 • Reliability and Validity for Multiple-Item Scales Test-Retest Reliability Factor Analysis Internal Reliability and Creating Scale Scores Chapter 13: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 13: R Instructions to Accompany Warner (2020b) CHAPTER 14 • Repeated-Measures Tests: Further Exploration Checking Assumptions One-Way Repeated-Measures Analysis of Variance Mixed Analysis of Variance Chapter 14: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 14: R Instructions to Accompany Warner (2020b) CHAPTER 15 • Brief Introduction to Latent-Variable Structural Equation Modeling Measurement Models Mediation With Latent-Variable Structural Equation Modeling Chapter 15: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 15: R Instructions to Accompany Warner (2020b) CHAPTER 16 • Binary Logistic Regression Getting Familiar With the Data Binary Logistic Regression Presenting Results Chapter 16: Summary of Key Functions (AKA: Function Cheat Sheet) Appendix 16: R Instructions to Accompany Warner (2020b) CHAPTER 17 • Additional Statistical Techniques Dealing With Time Dealing With Odd Distributions Dealing With Interdependence Concluding Thoughts References

      Recently viewed products

      © 2026 Book Curl

        • American Express
        • Apple Pay
        • Diners Club
        • Discover
        • Google Pay
        • Maestro
        • Mastercard
        • PayPal
        • Shop Pay
        • Union Pay
        • Visa

        Login

        Forgot your password?

        Don't have an account yet?
        Create account