# Significance Testing Principles

• ### Statistical Inference for Binomial Parameters

This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following:  Wald test, score test, likelihood-ratio test, large sample confidence intervals, and the F distribution.

• ### Penn State STAT 800: Introduction to Applied Statistics

This is a graduate level introduction to statistics including topics such as probabilty/sampling distributions, confidence intervals, hypothesis testing, ANOVA, and regression.  Perfect for students and teachers wanting to learn/acquire materials for this topic.

• ### Penn State STAT 509: Design and Analysis of Clinical Trials

This is a graduate level survey course that stresses the concepts of statistical design and analysis in biomedical research, with special emphasis on clinical trials. Perfect for students and teachers wanting to learn/acquire materials for this topic.

• ### HyperStat Online: Ch. 9 The Logic of Hypothesis Testing

This chapter explains the structure/steps of hypothesis testing, the concept of significance, the relationship between confidence intervals and hypothesis testing, and Type I/II errors.

• ### HyperStat Online: Ch. 10 Testing Hypotheses with Standard Errors

This text explains the differences between t-tests, z-tests, tests with proportions, and tests of correlation.

• ### HyperStat Online: Ch. 18 Measuring Effect Size

Measures of the size of an effect based on the degree of overlap between groups usually involve calculating the proportion of the variance that can be explained by differences between groups. This resource outlines different approaches to measuring this proportion.

• ### Rice Virtual Lab Simulations (JAVA Applets)

A collection of Java applets and simulations covering a range of topics (descriptive statistics, confidence intervals, regression, effect size, ANOVA, etc.).

• ### Song: Hypothesis on Trial

A song for use in helping students to identify counterparts in the courtroom analogy for hypothesis tests (innocence ≈ null; acquit ≈ fail to reject; etc…) and to identify errors of Type I and II in context.  Lyrics by Larry Lesser and music by Larry Lesser and Dominic Sousa in 2015, both from The University of Texas at El Paso.  This song is part of an NSF-funded library of interactive songs that involved students creating responses to prompts that are then included in the lyrics (see www.causeweb.org/smiles for the interactive version of the song, a short reading covering the topic, and an assessment item).

• ### Song: Everything's Unusual

A song for use in helping students to reason about how larger sample sizes decrease the p-value, all else being equal.  Lyrics by Larry Lesser and music by Dominic Sousa in 2015, both from The University of Texas at El Paso.  This song is part of an NSF-funded library of interactive songs that involved students creating responses to prompts that are then included in the lyrics (see www.causeweb.org/smiles for the interactive version of the song, a short reading covering the topic, and an assessment item).

• ### Computational and Inferential Thinking: The Foundations of Data Science

This is the free online textbook for the Foundations of Data Science class at UC Berkeley for the Data 8 Project. Creators have used https://github.com/data-8/textbook to maintain this textbook (an open source project that allows for continual easy editing and maintenance).