t-tests and ANOVA both aim to state if two different groups are different. Thus, they rely on data that can be split based on some discrete categories, such as whether the data comes from a pre-test or a post-test, or whether the data comes from a first-year student or a second-year student.

However, what if our explanatory variable is continuous instead of discrete? What if, for example, we wanted to see if class performance varied as a function of number of forum contributions or time spent watching videos? In this case, we would be looking at regression. The simplest form of regression is linear regression, where one variable is assumed to be a linear function of another.

For some information on linear regression, see these sources:

- Simple Linear Regression, from Penn State University
- Linear Regression, from Yale University
- Introduction to Linear Regression, from David Lane of Rice University

As with t-tests and ANOVA, you generally need not perform linear regressions by hand. Instead, here are some calculators or sources on how to carry them out more easily:

- Linear Regression Calculator, from GraphPad
- Simple Linear Regression Using Excel (Video), from Joseph Snider

For more comprehensive information, see:

- Research Methods in Education (Chapter 10)

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