ABSTRACT
Statistics is as much an art as a science. There is never just one way to analyze your data, which is why it’s important to understand the reasoning behind the use of various tests. In my own research I often find myself revising my statistical analysis when I take a fresh look at it after setting it aside for some months. I may discover an alternative test, or a different idea for looking at the data. Part II of the text will cover in depth a number of basic statistical tests including correlation, regression, t-tests, ANOVA, and chi-square tests. These are by no means all of the statistical tools that are available for analyzing data, but they are the basic ones that are used most frequently in the second language research literature.
