R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data. The purpose of R by Example is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics.
Specifically, R by Example is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data and R by Example is intended to be a useful resource for learning how to implement these procedures in R.
- Quantitative Data
- Categorical Data
- Presentation Graphics
- Exploratotry Data Analysis
- Basic Inference Models
- Analysis of Variance I
- Analysis of Variance II
- Randomiczation tests
- Simulation Experiments
- Bayesian Modeling
- Monte Carlo Methods
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Maria Rizzo is Associate Professor in the Department of Mathematics and Statistics at Bowling Green State University. Jim Albert is Professor of Mathematics and Statistics at Bowling Green State University.
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