Applied Statistics with Resampling Methods and R

An introductory statistical science book taught within a data analytic framework in R. Topics covered include descriptive statistics and randomization tests and bootstrapping for statistical inference.

Bruce Blaine

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Applied Statistics with Resampling Methods and R is intended to support an introductory undergraduate statistics or data science course, particularly those that emphasize data analysis and statistical computing. It covers statistics for doing univariate and bivariate descriptive analysis, including robust descriptive statistics. The book uses resampling methods (randomization and bootstrapping) for statistical inference, including methods for hypothesis testing and parameter estimation in several type of study designs. Data analytic examples are used to teach statistical concepts throughout, and students are introduced to the R packages and functions needed for basic data analysis. Each chapter includes data analytic problems for practice or assessment. R script, data, and metadata files are available by chapter at github.com/bblaine6.

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Bruce Blaine

Bruce Blaine, PhD, PStat® is a Professor at St. John Fisher College in Rochester, NY with training in statistics and behavioral science. He teaches undergraduate and graduate courses in statistics, data analysis, and quantitative research methods.

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