Routledge

A Guide to Doing Statistics in Second Language Research Using R

by Jenifer Larson-Hall


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Note:
This guide is meant as a companion to Jenifer Larson-Hall's book A Guide to Doing Statistics in Second Language Research Using SPSS (Routledge, 2010).  We have sought to make the structure of the R guide correspond to the structure of the SPSS book as much as possible.  However, some chapters in the SPSS book do not have corresponding chapters in the R guide.  Therefore, there is no Chapter 2, 4 or 5 in the R guide.


Quick Reference Document

To help you navigate A Guide to Doing Statistics in Second Language Research Using R this Quick Reference Document contains a brief description of each section's contents, and its corresponding section/page in A Guide to Doing Statistics in Second Language Research Using SPSS.


Full book

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By chapter

Front matter

Introduction, Table of Contents, List of R Packages Used


Chapter 1 — Getting Started with R
  • 1.1¬†¬† Downloading & Opening
  • 1.2¬†¬† Working with Data
  • 1.3¬†¬† Application Activity: Practice Entering Data
  • 1.4¬†¬† Introduction to R Workspace¬†¬† ¬†¬†¬†¬†¬†¬†¬†¬†¬†
  • 1.5¬†¬† Missing Data
  • 1.6¬†¬† Application Activity: Saving Data
  • 1.7¬†¬† Getting Help
  • 1.8¬†¬† R as a Calculator
  • 1.9¬†¬† Application Activity: Using R as a Calculator
  • 1.10¬†¬† Objects
  • 1.11¬†¬† Application Activity: Creating objects
  • 1.12¬†¬† Types of Data in R
  • 1.13¬†¬† Application Activity: Types of Data
  • 1.14¬†¬† Functions in R
  • 1.15¬†¬† Application Activity: Functions
  • 1.16¬†¬† Manipulating Variables (Advanced Topic)
  • 1.17¬†¬† Application Activity: Manipulating Variables
  • 1.18¬†¬† Random Number Generation


THERE IS NO CHAPTER 2


Chapter 3 — Describing Data
  • 3.1¬†¬† Obtaining Numerical Summaries
  • 3.2¬†¬† Application Activity: Numerical Summaries
  • 3.3¬†¬† Generating Histograms, Stem and Leaf Plots, and Q-Q Plots
  • 3.4¬†¬† Application Activity: Exploring Assumptions
  • 3.5¬†¬† Transformations
  • 3.6¬†¬† Application Activity: Transformations


THERE IS NO CHAPTER 4 or CHAPTER 5


Chapter 6 — Correlation
  • 6.1¬†¬† Creating Scatterplots
  • 6.2¬†¬† Application Activity: Creating Scatterplots
  • 6.3¬†¬† Calculating Coefficients
  • 6.4¬†¬† Application Activity: Calculating Coefficients
  • 6.5¬†¬† Partial Correlation
  • 6.6¬†¬† Point-Biserial Correlations and Interrater Reliability

Chapter 7 — Multiple Regression
  • 7.1¬†¬† Graphs for Understanding Complex Relationships
  • 7.2¬†¬† Application Activity: Graphs for Understanding Complex Relationships
  • 7.3¬†¬† Doing the Same Type of Regression as SPSS
  • 7.4¬†¬† Application Activity: Multiple Regression
  • 7.5¬†¬† Finding the Best Fit
  • 7.6¬†¬† Further Steps in Finding the Best Fit
  • 7.7¬†¬† Examining Regression Assumptions
  • 7.8¬†¬† Application Activity: Finding the Best Fit
  • 7.9¬†¬† Robust Regression
  • 7.10¬†¬† Application Activity: Robust Regression

Chapter 8 — Chi-square
  • 8.1¬†¬† Summarizing and Visualizing Data
  • 8.2¬†¬† Application Activity: Summarizing and Visualizing Data
  • 8.3¬†¬† One-Way Goodness of Fit Test
  • 8.4¬†¬† Two-Way Group Independence Test
  • 8.5¬†¬† Application Activity: Chi-square Tests

Chapter 9 — T-tests
  • 9.1¬†¬† Creating Boxplots
  • 9.2¬†¬† Application Activity: Creating Boxplots
  • 9.3¬†¬† The Independent-Samples T-test
  • 9.4¬†¬† A Robust Independent-Samples T-test
  • 9.5¬†¬† Application Activity: Independent-Samples T-tests
  • 9.6¬†¬† The Paired-Samples T-test
  • 9.7¬†¬† A Robust Paired-Samples T-test
  • 9.8¬†¬† Application Activity: Paired-Samples T-tests
  • 9.9¬†¬† The One-Sample T-test
  • 9.10¬†¬† A Robust One-Sample T-test
  • 9.11¬†¬† Application Activity: One-Sample T-tests

Chapter 10 — One-Way ANOVA
  • 10.1¬†¬† Visual Summary with Boxplots Overlaid with Dotcharts
  • 10.2¬†¬† Application Activity: Boxplots Overlaid with Dotcharts
  • 10.3¬†¬† One-Way ANOVA Test
  • 10.4¬†¬† A Robust One-Way ANOVA Test
  • 10.5¬†¬† Application Activity: One-Way ANOVAs

Chapter 11 — Factorial ANOVA
  • 11.1¬†¬† Visual Summary with Means Plots
  • 11.2¬†¬† Putting Data in Correct Format for Factorial ANOVA
  • 11.3¬†¬† Factorial ANOVA Test
  • 11.4¬†¬† Performing Comparisons in a Factorial ANOVA
  • 11.5¬†¬† Application Activity: Factorial ANOVA
  • 11.6¬†¬† Robust ANOVA

Chapter 12 — Repeated Measures ANOVA
  • 12.1 Visualizing Data
  • 12.2¬†¬† Application Activity: Interaction Plots and Parallel Coordinate Plots
  • 12.3¬†¬† Putting Data in Correct Format for RM ANOVA
  • 12.4¬†¬† Performing an RM ANOVA the Fixed-Effects Way
  • 12.5¬†¬† Performing an RM ANOVA the Mixed-Effects way
  • 12.6¬†¬† Application Activity: Mixed-Effect models

Chapter 13 — ANCOVA
  • 13.1¬†¬† One-Way ANCOVA with One Covariate
  • 13.2¬†¬† Two-Way ANCOVA with Two Covariates
  • 13.3¬†¬† Robust ANCOVA
  • 13.4¬†¬† Application Activity: ANCOVA

Appendices

Appendix A: Doing Things in R

A collection of ways to do things in R gathered into one place. Some are found in various places in the text while others are not, but they are collected here. Examples are 'finding out names of a dataset', 'changing data from one type to another' and 'Order data in a dataframe'. Ideas for troubleshooting are also included.

Appendix B: Calculating the FDR

Calculate p-value cut-offs for adjusting for multiple tests (the FDR algorithm is much more powerful than conventional tests like Tukey's HSD or Scheffe)

Appendix C: Using Wilcox's R library

How to get commands for robust tests using the Wilcox WRS library into R.


Bibliography
Book Information / Buy the book