Description
Book SynopsisLearn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical methods. This in-depth tutorial includes key R 4 features including a new color palette for charts, an enhanced reference counting system (useful for big data), and new data import settings for text (as well as the statistical methods to model text-based, categorical data).
Each chapter starts with a list of learning outcomes and concludes with a summary of any R functions introduced in that chapter, along with exercises to test your new knowledge. The text opens with a hands-on installation of R and CRAN packages for both Windows and macOS. The bulk of the book is an introduction to statistical methods (non-proof-based, applied statistics) that relies heavily on R (and R visualizations) to understand, motivate, and conduct statistical tests and modeling.
Beginning R 4 shows the use of R in specific cases such as ANO
Table of Contents
1: Installing R2: Installing Packages and Using Libraries3: Data Input and Output4: Working with Data5: Data and Samples6: Descriptive Statistics7: Understanding Probability and Distribution8: Correlation and Regression9: Confidence Intervals10: Hypothesis Testing11: Multiple Regression12: Moderated Regression13: Analysts of VarianceBibliography
