Statistics Using R
An Integrative Approach
Published on 13. August 2020
Book
Paperback/Softback
692 pages
978-1-108-71914-8 (ISBN)
Description
Using numerous examples with real data, this textbook closely integrates the learning of statistics with the learning of R. It is suitable for introductory-level learners, allows for curriculum flexibility, and includes, as an online resource, R-code script files for all examples and figures included in each chapter, for students to learn from and adapt and use in their future data analytic work. Other unique features created specifically for this textbook include an online R tutorial that introduces readers to data frames and other basic elements of the R architecture, and a CRAN library of datasets and functions that is used throughout the book. Essential topics often overlooked in other introductory texts, such as data management, are covered. The textbook includes online solutions to all end-of-chapter exercises and PowerPoint slides for all chapters as additional resources, and is suitable for those who do not have a strong background in mathematics.
Reviews / Votes
'... a good, comprehensive textbook in introductory statistics in R. It would be a good resource to teach students without a strong mathematical background about introductory statistics using base R.' Lauren Kennedy, Economic RecordMore details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
College/higher education
Product notice
Paperback (trade)
Illustrations
Worked examples or Exercises; 102 Tables, black and white; 4 Halftones, black and white; 184 Line drawings, black and white
Dimensions
Height: 200 mm
Width: 250 mm
Thickness: 35 mm
Weight
1440 gr
ISBN-13
978-1-108-71914-8 (9781108719148)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Sharon Lawner Weinberg | Daphna Harel | Sarah Knapp Abramowitz
Statistics Using R
An Integrative Approach
Book
12/2023
2nd Edition
Cambridge University Press
€91.00
Shipment within 15-20 days
Additional editions
Sharon Lawner Weinberg | Daphna Harel | Sarah Knapp Abramowitz
Statistics Using R
An Integrative Approach
E-Book
08/2020
Cambridge University Press
€65.99
Available for download
Persons
Sharon Lawner Weinberg is Professor of Applied Statistics and Psychology, and the former Vice Provost for Faculty Affairs, at New York University (NYU). She is the recipient of the NYU Steinhardt Outstanding Teaching Award, and has taught statistics at both undergraduate and graduate levels. Her research has been supported by federal agencies and private foundations. Daphna Harel is Associate Professor of Applied Statistics at New York University. She is known for her innovative approach to teaching both introductory and advanced statistics. Her research has been supported by federal agencies and foundations, such as the National Institutes for Health and the Canadian Institutes for Health Research. Sarah Knapp Abramowitz is Professor of Mathematics and Computer Science, Department Chair, and Co-ordinator of Statistics Instruction at Drew University. She is Associate Editor of the Journal of Statistics Education and has presented at national conferences on topics related to the teaching of statistics.
Content
Preface; Acknowledgments; 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; Appendix A. Data Set Descriptions; Appendix B. .R Files and Datasets in R Format; Appendix C. Statistical Tables; Appendix D. References; Appendix E. Solutions to End of Chapter Exercises; Index.