# Significance Testing Principles

• ### Blindfold Climbers

This article, in a series, describes a game, which tests opposing strategies through aspects of experiemental design.
• ### Deriving Regression Lines Without Calculus

This article describes a method to calculate the least squares line algebraically. First, the author uses a numeric example, which uses calculus, then describes a simpler algebraic method.
• ### The First shall be Last

This article provides the example of student form orders to demonstrate the unreliability of combining data from two different distributions (or subjects).
• ### Reading and Interpreting Tables and Graphs Involving Rates and Percentages

This survey assesses statistical literacy. The survey focuses on the general use of informal statistics in everyday situations: reading and interpreting tables and graphs involving rates and percentages.
• ### Time-Axis Fallacy and Bayes Theorem

This site provides an outline of an activity for introducing Bayes' Theorem and conditional probability.
• ### Tutorial: Using SPSS for t-tests.

This tutorial exposes students to conducting t-tests in SPSS. This html based tutorial provides extensive screen shots and two example data sets. Topics covered in the tutorial include one sample, paired and independent samples t-tests and conducting transformations (such as a difference) of the data.

• ### Analysis Tool: One Arm Binomial

This page calculates either sample size or power for a one sample binomial problem. Users choose between a one-sided and two-sided test and specify the null and alternative hypothesized proportions. The calculator also gives the critical value.

• ### Statistics at Square One: Differences Between Percentages and Paired Alternatives

This topic from an online textbook discusses standard error, confidence interval, and significance testing for a difference in percentages or proportions. It also covers paired alternatives and standard error of a total. Exercises and answers are also provided.
• ### Dataset Example: Data from the Television Game Show "Friend or Foe?"

This article describes data from the television game show Friend or Foe. The data can be used to determine factors affecting contestants' strategies using descriptive statistics, testing for differences in means or proportions, and regression analysis. Key Words: Discrete choice analysis.
• ### Data Collection: NFL Scores and Pointspreads

The datasets described in this article contain information for all National Football League (NFL)regular season and playoff games played from 1993 to 1996. In addition to game scores, the data give oddsmakers' pointspreads and over/under values for each game. Key Words: Predictions; Wagering.