Statistics Using R An Integrative Approach

About this book

Statistics Using R introduces the most up-to-date approaches to R programming alongside an introduction to applied statistics using real data in the behavioural, social, and health sciences. It is uniquely focused on the importance of data management as an underlying and key principle of data analysis. It includes an online R tutorial for learning the basics of R, as well as two R files for each chapter, one in Base R code and the other in tidyverse R code, that were used to generate all figures, tables, and analyses for that chapter. These files are intended as models to be adapted and used by readers in conducting their own research. Additional teaching and learning aids include solutions to all end-of-chapter exercises and PowerPoint slides to highlight the important takeaways of each chapter. Statistics Using R is appropriate for both undergraduate and graduate students in social sciences, applied statistics, and research methods.

Contents

1. Introduction
2. Examining Univariate Distributions
3. Measures of Location, Spread, and Skewness
4. Re-Expressing Variables
5. Exploring Relationships between Two Variables
6. Simple Linear Regression
7. Probability Fundamentals
8. Theoretical Probability Models
9. The Role of Sampling in Inferential Statistics
10. Inferences Involving the Mean of a Single Population when is Known
11. Inferences Involving the Mean When is Not Known: One- and Two-Sample Designs
12. Research Design: Introduction and Overview
13. One-Way Analysis of Variance
14. Two-Way Analysis of Variance
15. Correlation and Simple Regression as Inferential Techniques
16. An Introduction to Multiple Regression
17. Two-Way Interactions in Multiple Regression
18. Nonparametric Methods
19. Accessing Data from Public Use Sources

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Biography

Sharon L. Weinberg is Professor of Applied Statistics and Psychology at New York University and formerly Vice Provost for Faculty Affairs at New York University, USA. She has taught, over many years in higher education, a broad range of statistics courses at both the undergraduate and graduate levels, from introductory to advanced. She is a recipient of the NYU Steinhardt Teaching Excellence Award, the NYU Steinhardt Daniel Griffiths Award for Distinguished Research, and a four-time recipient of the Outstanding Reviewer Award for her work on the Editorial Board of the Educational Researcher, American Educational Research Association's (AERA's) flagship journal, as a reviewer of manuscripts submitted for publication. Her research has been supported by grants from both federal and private agencies, including the IES, NSF, and the Sloan Foundation, and she has published numerous papers on her research. She is the co-editor with NYU colleague Lisa Stulberg of Diversity in American Higher Education: Toward a More Comprehensive Approach (Routledge, 2011). She has also published numerous expository papers on methodology as book chapters and journal articles.

Daphna Harel is an Associate Professor of Applied Statistics at New York University, USA. She is known for her innovative pedagogical approach to the teaching of statistics, from the introductory undergraduate to the advanced graduate level. She earned her BSc and PhD from the McGill University Department of Mathematics and Statistics, Canada. Her research has been supported by federal agencies and foundations, such as the National Institutes of Health, the Canadian Institutes for Health Research, and the Spencer Foundation. As a highly productive researcher, she has published numerous peer-reviewed articles across statistics, as well as several domain areas.

Sarah Knapp Abramowitz is the John H. Evans Professor and Chair of the Department of Mathematics and Computer Science at Drew University, USA. She earned an A.B. in Mathematics from Cornell University and a Ph.D. in Mathematics Education from New York University, USA. She is an Associate Editor of the Journal of Statistics and Data Science Education and has published expository papers and presented at national conferences on topics related to the teaching of statistics. She is currently teaching an undergraduate course in statistics that uses this text along with a flipped approach, in which students watch instructor-created videos outside of class and spend class time participating in student-centred, activity-based learning.