Learning Statistics Using R

Description

Providing easy-to-use R script programs that teach descriptive statistics, graphing, and other statistical methods, Learning Statistics Using R shows readers how to run and utilize R, a free integrated statistical suite that has an extensive library of functions. Schumacker’s comprehensive book describes the processing of variables in statistical procedures. Covering a wide range of topics, from probability and sampling distribution to statistical theorems and chi-square, this introductory book helps readers learn not only how to use formulae to calculate statistics, but also how specific statistics fit into the overall research process. Each chapter includes discussion and explanations, tables and graphs, and R functions and outputs to enrich readers′ understanding of statistics through statistical computing and modeling. Brief Contents Detailed Contents About the Author Preface Acknowledgments PART I. INTRODUCTION AND BACKGROUND 1. R Basics 2. Research Methods 3. Probability 4. Sampling and Populations PART II. STATISTICAL THEORY AND INFERENCE 5. Population Distributions 6. Sampling Distributions 7. Statistical Distributions PART III. DESCRIPTIVE METHODS 8. Graphing Data 9. Central Tendency and Dispersion PART IV. STATISTICAL METHODS 10. Hypothesis Testing 11. Chi-Square Test for Categorical Data 12. z Test for Differences in Proportions 13. t Test for Mean Differences (Two Groups) 14. F Test for Mean Differences (Three or More Groups) 15. Correlation Tests of Association 16. Linear Regression Tests of Prediction 17. Multiple Regression 18. Logistic Regression 19. Log-Linear Regression PART V. REPLICATION AND VALIDATION OF RESEARCH FINDINGS 20. Replication of Statistical Tests 21. Synthesis of Research Findings Glossary of Terms Glossary of Packages, Functions, and Commands Used in the Book Appendix A: Statistical Tables Appendix B: Guide for Selecting a Statistical Test References Author Index Subject Index