# Significance Testing Principles

• ### Alpha Level (Significance Level): What is it?

Text resource that covers what type I and II errors are, how to Calculate an Alpha Level for one- and two-tailed tests, and why an Alpha Level of .05 commonly used. There is also a video included at the beginning of the video to explain the topics.
• ### Type I and II Error and Significance Level

Covers topics of type I and II errors and significance levels. Common mistakes for these topics are given and the reasons they are incorrect are explained.
• ### Hypothesis Test Notes: P-value and Significance Level

Notes on hypothesis testing and how to interpret the p-value with respect to the significance level of a hypothesis test.
• ### Understanding Significance Level in Hypothesis Testing

Resource that explains the importance of the significance level in hypothesis testing, statistical significant results and significance levels, and type I and errors and level of significance.
• ### Level of Significance

Definition of significance and the steps to determining the significance level of a test.
• ### Two-Sided Testing and C.I. s; Choosing the Levels of Significance

Powerpoint that covers statistical testing and choosing the level of significance. It also shows statistical significance vs. practical significance.
• ### Hypothesis Tests

Covers many topics within Hypothesis Testing, with a section dedicated to Significance level.
• ### Confidence Intervals - Level of Significance

Simple definition of the level of significance, with an explanation as to how it differs from the confidence level.
• ### Cartoon: P-value Interpretations

A cartoon suitable for use in discussing the interpretation of p-values of different levels. The cartoon is number 1478 (January, 2015) from the webcomic series at xkcd.com created by Randall Munroe. Free to use in the classroom and on course web sites under a creative commons attribution-non-commercial 2.5 license.

• ### Quote: Wollstonecraft on Hypotheses

A quote to be used in discussing how sufficient data should be able to trump an hypothesis. The quote is by English philosopher and pioneering feminist Mary Wollstonecraft (1759 â€“ 1797) from her 1792 book "A Vindication of the Rights of Woman." .