Regression

  • 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.
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  • This tutorial explains in detail how to perform an ANOVA in Excel.
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  • This tutorial explains in detail how to find a confidence interval using Excel.
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  • This tutorial explains in detail how to make a scatterplot in Excel.
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  • 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.
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  • This applet demonstrates how the reliability of X and Y affect various aspects of the regression of Y on X.
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  • This is a simulation illustrating the regression toward the mean phenomenon.
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  • 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.
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  • This case study assesses the question, "Can the application of magnetic fields be an effective treatment for pain?" It addresses concepts including: boxplots, stem and leaf displays, correlated t-test, two-sample t-test, repeated measures analysis of variance, and analysis of covariance.
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  • This case study addresses the question: "Will a smiling person accused of a crime be treated more leniently than one who is not smiling? If so, does the type of smile make a difference?" It concerns the following concepts: quantile/boxplots, contrasts among means, Dunnett's test, and Bonferroni correction.
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