# 1st Edition Resources

## SPSS Data Sets

This is raw data used to complete exercises in book. The .sav files open in the SPSS program. Files are compatible with both PC and Mac.

- Read
- Write
- GeeslinGF3_5
- HowellChp15Data
- InagakiLong1999.Ttest
- InagakiLong
- Lafrance5
- LafranceGottardo
- Language Choice
- LarsonHall2004
- LarsonHall2008
- LarsonHall.Forgotten
- LarsonHallGJT
- LarsonHallPartial
- LeowMorganShort
- Lyster.Oral
- Lyster.Written
- MackeySilver2005
- Motivation
- MunroDerwingMorton
- Murphy.RepeatedMeasures
- Obarow.Original
- Obarow
- Obarow.Story1
- Obarow.Story2
- Pandey2000
- Torres
- Yates2003
- BeautifulRose
- BEQ.Context
- BEQ.Dominance
- BEQ
- BEQ.Swear
- ClassTime
- DeKeyser2000
- EllisYuan
- Erdener&Burnham2005
- Eysenck.HowellChp13
- FlegeYeniKomshianLiu
- FlegeYKLiu
- French & O'Brien grammar

## Useful Websites

http://www.spss.com/statistics/

Buy SPSS or get a free 30-day trial.

http://www.psychwiki.com/wiki/Want_help_using_SPSS%3F

This link gives you lots of places to start looking for help with using SPSS.

http://www.ats.ucla.edu/stat/spss/

A web page from UCLA that walks you through some helpful steps for doing things in SPSS, including more advanced topics than are treated in this book, such as logistic regression and multilevel modeling (also called “hierarchical modeling”).

http://www.spsstools.net/

A personal website where the author has collected lots of scripts that can be implemented in SPSS to increase your computing power. It includes a “Newbie's Corner.”

http://www.listserv.uga.edu/archives/spssx-l.html

A listserv where you can search for tips about using SPSS. You can post questions to the listserv and also sign up to receive a daily feed of questions and answers. If you are interested in more advanced uses of SPSS, this would be a good place to start.

## Errata List

p. 64, section 3.1.1. In calculations of the sum of squares, the second number should be 354, not 351.

p. 130, section 5.1. Chi-square is generally classified as a test of relationships (cf. the table from Hatch and Lazaraton’s *The Research Manual*, reprinted in Porte, 2002, p. 284-285. However, in 5.1 I classify it as a test of group differences (it is correctly labeled as a test of relationships on p. 135).

p.208, in Table 8.3, under the “German” column, the results of 100*39/200 should be 19.5 instead of 18.5

p.209, in the equation, the fourth item (German) should have the expected score as 19.5. Also, only the data from Hometown U are included, not the data from Big City University (the second line of the equation looks to be just a repetition of the first line). However, the final result of the equation, 8.374, is correct.

p.270, the last line of the first paragraph should read “the different levels in the independent variable”, as is seen in figure 10.3 on the next page.

p. 285, section 10.5.4, second paragraph: The output for calculating the PV comes from Table 10.5, not Figure 10.10, and the PV should be calculated as 240.9/759.9 (this results correctly in .32).

p. 334, section 12.2.1, Table 12.1. Line 10 of the syntax for this plot should have the word “Cond” underlined after the word “DATA:” as this will need to be replaced with the user’s own label for the group-splitting variable.

## 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*.

Full book

Download A Guide to Doing Statistics in Second Language Research Using R

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

## R Data Sets

This is raw data used to complete exercises in the R guide. The .sav files open in the R program. Files are compatible with both PC and Mac.