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# Regression

• ### DIG Stats: Graphical Analysis

This module contains discussions on two and three dimensional graphs, histograms, scatterplots, boxplots, and data visualization, and provides links to a variety of relevant activities.
• ### Data Collection: Journal of Statisitcs Education - Data Archive

The Journal of Statistics Education has published this collection of datasets and related articles describing their use, submitted by faculty members from numerous institutions. Data is in .dat format.
• ### DIG Stats: Insulation Activity

In this activity, students will generate scatterplots and use regression and logarithms to explore a dataset with time and temperature data for an insulation pack. Questions about the exercise are given at the bottom of the page as well as links to instructions for Excel and the TI-83 calculator. The data exists in TI-83 group, Excel, and text formats.
• ### DIG Stats: Excel Guide for Performing an ANOVA

This tutorial explains in detail how to perform an ANOVA in Excel.
• ### DIG Stats: Excel Guide for Determining the Confidence Interval

This tutorial explains in detail how to find a confidence interval using Excel.
• ### DIG Stats: Excel Guide for Making a Scatterplot

This tutorial explains in detail how to make a scatterplot in Excel.
• ### Data+Applet : Regression by Eye

In this demonstration a scatterplot is displayed and you draw in a regression line by hand. You can then compare your line to the best least squares fit. You can also try to guess the value of Pearson's correlation coefficient.
• ### Dataset Example: Reliability and Regression Analysis

This applet demonstrates how the reliability of X and Y affect various aspects of the regression of Y on X.
• ### Regression to the Mean

This is a simulation illustrating the regression toward the mean phenomenon.
• ### Weapons and Aggression

This case study addresses the question: "Does the mere presence of a weapon increase the accessibility of aggressive thoughts?" It concerns the following concepts: quantile and box plots, stem and leaf displays, one-sample t test, confidence interval, within-subjects ANOVA, and consequences of violation of normality assumption.