IX. Logic of Hypothesis Testing
Prerequisites
none
- Introduction
- Significance
Testing
- Type
I and Type II Errors
- One-
and Two-Tailed Tests
- Interpreting
Significant Results
- Interpreting
Non-Significant Results
- Steps
in Hypothesis Testing
- Significance Testing
and Confidence Intervals
- Misconceptions
- Exercises
- PDF
Files (in .zip archive)
When interpreting an experimental finding, a natural question arises
as to whether the finding could have occurred by chance. Hypothesis
testing is a statistical procedure for testing whether chance
is a plausible explanation of an experimental finding. Misconceptions
about hypothesis testing are common among practitioners as well
as students. To help prevent these misconception, this chapter
goes into more detail about the logic of hypothesis testing than
is typical for an introductory-level text.
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