Database Reference
In-Depth Information
Summary
R is a popular package and programming language for data exploration, analytics,
and visualization. As an introduction to R, this chapter covers the R GUI, data
I/O, attribute and data types, and descriptive statistics. This chapter also discusses
how to use R to perform exploratory data analysis, including the discovery of dirty
data, visualization of one or more variables, and customization of visualization for
different audiences. Finally, the chapter introduces some basic statistical methods.
The first statistical method presented in the chapter is the hypothesis testing. The
Student's t -test and Welch's t -test are included as two example hypothesis tests
designed for testing the difference of means. Other statistical methods and tools
presented in this chapter include confidence intervals, Wilcoxon rank-sum test, type
I and II errors, effect size, and ANOVA.
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