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An Introduction to R

In: Bayesian Computation with R

Author

Listed:
  • Jim Albert

    (Bowling Green state University)

Abstract

R is a rich environment for statistical computing and has many capabilities for exploring data in its base package. In addition, R contains a collection of functions for simulating and summarizing the familiar one-parameter probability distributions. One goal of this chapter is to provide a brief introduction to basic commands for summarizing and graphing data. We illustrate these commands on a dataset about students in an introductory statistics class. A second goal of this chapter is to introduce the use of R as an environment for programming Monte Carlo simulation studies. We describe a simple Monte Carlo study to explore the behavior of the two-sample t statistic when testing from populations that deviate from the usual assumptions. We will find these data analysis and simulation commands very helpful in Bayesian computation.

Suggested Citation

  • Jim Albert, 2009. "An Introduction to R," Springer Books, in: Bayesian Computation with R, chapter 1, pages 1-17, Springer.
  • Handle: RePEc:spr:sprchp:978-0-387-92298-0_1
    DOI: 10.1007/978-0-387-92298-0_1
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