Statistics Using R (2nd ed.)

Statistics Using R: An Integrative Approach 2nd Edition, Kindle Edition

Description:
Statistics Using R: An Integrative Approach, 2nd Edition, introduces readers to the most current methods in R programming while teaching applied statistics using real data from the behavioral, social, and health sciences. This textbook emphasizes the importance of data management as a key foundation for effective data analysis, ensuring readers develop essential skills for handling, cleaning, and analyzing data sets. Each chapter includes two R code files (Base R and tidyverse R) that were used to generate all figures, tables, and analyses, allowing readers to adapt these files for their own research projects.

Additional features of this edition include an online R tutorial, solutions to all end-of-chapter exercises, and PowerPoint slides to emphasize the main takeaways from each chapter. Ideal for both undergraduate and graduate students in social sciences, applied statistics, and research methods, this textbook offers comprehensive resources for mastering R programming and statistical analysis.

The 2nd edition has been updated to reflect the latest developments in statistical methods and the R language, making it a go-to resource for both beginner and intermediate users of R. Whether you are a student or a professional looking to enhance your data analysis skills, this book provides a practical, integrative approach to statistics using real-world examples from various scientific fields.

Table of Contents (Short Version)

1. Introduction to R and Data Management
2. Descriptive Statistics and Data Visualization
3. Probability and Sampling Distributions
4. Hypothesis Testing and Confidence Intervals
5. Regression Analysis
6. Analysis of Variance (ANOVA)
7. Nonparametric Methods
8. Logistic Regression
9. Multivariate Analysis
10. Advanced Topics in R Programming

Why Is Data Management Important in Statistics?

Data management is a critical aspect of statistics because it involves collecting, storing, and organizing data in a way that ensures its accuracy, accessibility, and consistency. Proper data management ensures that data is clean, reliable, and ready for analysis, which is crucial for drawing valid conclusions from statistical studies. By effectively managing data, statisticians can avoid errors, streamline their analysis process, and ensure that the results they produce are replicable and trustworthy.

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Product Details:

• Publisher: Cambridge University Press
• Published: December 2023
• ISBN: 9781009400152
• Edition: 2
• Language: English
• Number of Pages: 726