European University Institute Library

Learning statistics using R, Randall E. Schumacker, The University of Alabama

eng

Includes bibliographical references and indexes

illustrations

index present

non fiction

Learning statistics using R

bibliography

903104497

Randall E. Schumacker, The University of Alabama

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. Randall E. Schumacker's comprehensive book describes in detail 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. Learning Statistics Using R covers data input from vectors, arrays, matrices and data frames, as well as the input of data sets from SPSS, SAS, STATA and other software packages. Schumacker's text provides the freedom to effectively calculate, manipulate, and graphically display data, using R, on different computer operating systems without the expense of commercial software. Learning Statistics Using R places statistics within the framework of conducting research, where statistical research hypotheses can be directly addressed. 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.--, Provided by Publisher

PART I. Introduction and Background 1. R Basics 2. Research Methods 3. Probability 4. Sampling and Populations PART II. Statistical Theory and Inference 5. Central Limit Theorem 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 (2 groups) 14. F Test for Mean Differences (3 or more groups) 15. Correlation Tests of Association 16. Linear Regression Tests of Prediction 17. Multiple Regression 18. Logistic Regression 19. Loglinear 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 Book Statistical Tables Guide for Selecting a Statistical Test