A Guide to Doing Statistics in Second Language Research Using SPSS

A Guide to Doing Statistics in Second Language Research Using R

by Jenifer Larson-Hall

You may download the entire guide or individual chapters by clicking on the links below.

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.

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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.