Chapter 1 Introduction 1.1 Sample questions in foreign language education 1.2 Basic terms 1.3 Scales of measurement 1.4 Types of data 1.5 Descriptive statistics and inferential statistics 1.6 Summary Chapter 2 Examining data 2.1 Frequency distributions 2.2 Measures of central tendency 2.3 Measures of variability 2.4 Using the SPSS software program to manage and examine a dataset 2.5 Summary Chapter 3 Z scores and the normal distribution 3.1 The z score 3.2 Characteristics of z scores 3.3 Computation of z scores with SPSS 3.4 Empirical and theoretical frequency distributions 3.5 The normal distribution table 3.6 Summary Chapter 4 Sampling distributions and confidence intervals 4.1 Sampling methods 4.2 The sampling distribution 4.3 Central Limit Theorem 4.4 Calculating the standard error of the sampling distribution of means 4.5 Calculating the proportion of sample means above or below a certain point 4.6 Confidence intervals about a population mean 4.7 The t distribution 4.8 Summary Chapter 5 Hypothesis testing: One-sample designs 5.1 Procedure of the one-sample t test 5.2 The meaning of p 5.3 Effect size index 5.4 Use the SPSS software program to run the one-sample t test 5.5 Summary Chapter 6 Hypothesis testing: Two-samples designs 6.1 Independent-samples designs and paired-samples designs 6.2 The t test for independent-samples designs 6.3 Assumptions of the independent-samples t test 6.4 Using SPSS to run the t-test for independent-samples designs 6.5 Calculation of effect sizes for independent-samples designs 6.6 The t test for related-samples designs 6.7 Using SPSS to run the t-test for related-samples designs 6.8 Calculation of effect sizes for two related-samples designs 6.9 Summary Chapter 7 Correlation and regression 7.1 Correlation 7.2 The correlation coefficient 7.3 Effect sizes of correlation coefficients 7.4 Assumptions for the Pearson product-moment correlation (r)
7.5 Using SPSS to compute a Pearson correlation(r) 7.6 Using correlation coefficients to calculate coefficient of determination 7.7 Other kinds of correlation coefficients 7.8 Bivariate regression 7.9 A least squares regression line 7.10 Using SPSS for bivariate regression analysis 7.11 Multiple regression 7.12 Using SPSS for multiple regression analysis 7.13 Summary Chapter 8 Chi square tests 8.1 The chi square distribution 8.2 The use of chi square tests 8.3 Compute chi square values and examine the effect size 8.4 Chi square effect size coefficients 8.5 Using SPSS to conduct chi square tests of independence 8.6 Using SPSS to conduct chi square tests of goodness-of-fit 8.7 Summary Chapter 9 One way analysis of variance (ANOVA) 9.1 The rationale of ANOVA 9.2 The F distribution 9.3 Using SPSS to conduct ANOVA 9.4 Post hoc multiple comparison tests 9.5 Effect size indexes 9.6 Summary Chapter 10 Power analysis 10.1 Power and types of power analyses 10.2 Functions of power analyses 10.3 Ways to improve power 10.4 Using SPSS to conduct a post hoc power analysis 10.5 Summary Chapter 11 Two nonparametric tests 11.1 Comparison of nonparametric to parametric tests 11.2 The Mann-Whitney U test 11.3 Using SPSS to conduct Mann-Whitney U tests 11.4 The Wilcoxon matched-pairs signed-ranks test 11.5 Using SPSS to conduct Wilcoxon matched-pairs signed-ranks tests 11.6 Summary Chapter 12 Selecting appropriate statistical methods 12.1 Selection of appropriate descriptive statistical methods 12.2 Selection of appropriate inferential statistical methods Appendix A Answers to exercises Appendix B Quick reference guide to frequently asked questions Appendix C Glossary Appendix D The normal distribution table Appendix E The t distribution table Appendix F Critical values for the F mux statistic Appendix G Critical values for Pearson product-moment correlation coefficients, r Appendix H Chi square distribution table Appendix I The F distribution table Appendix J Power tables
Appendix K Sample size tables Appendix L Critical values for the Mann-Whitney U test Appendix M Critical values for the Wilcoxon matched-pairs signed-ranks T test References
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