Non-symbolic math

  • This page discusses the proper procedures for multiple comparison tests and reasons behind them.
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  • This collection of tutorials covers many statistical applications such as Pearson's Correlation Coefficient, Simple Linear Regression, One and Two Sample t-tests, Paired t-test, One-way Analysis of Variance (ANOVA), Mann-Whitney Test, Kruskal-Wallis Test, Friedman's Test, Interpreting p-values, Comparing two groups, Parametric and Nonparametric analyses, and Multiple Comparisons. The tutorials refer to the WINKS statistical software program, but they are useful for those who do not have access to WINKS.
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  • Using cooperative learning methods, this activity provides students with 24 histograms representing distributions with differing shapes and characteristics. By sorting the histograms into piles that seem to go together, and by describing those piles, students develop awareness of the different versions of particular shapes (e.g., different types of skewed distributions, or different types of normal distributions), and that not all histograms are easy to classify. Students also learn that there is a difference between models (normal, uniform) and characteristics (skewness, symmetry, etc.).
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  • Using cooperative learning methods, this lesson introduces distributions for univariate data, emphasizing how distributions help us visualize central tendencies and variability. Students collect real data on head circumference and hand span, then describe the distributions in terms of shape, center, and spread. The lesson moves from informal to more technically appropriate descriptions of distributions.
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  • Using cooperative learning methods, this activity helps students develop a better intuitive understanding of what is meant by variability in statistics. Emphasis is placed on the standard deviation as a measure of variability. This lesson also helps students to discover that the standard deviation is a measure of the density of values about the mean of a distribution. As such, students become more aware of how clusters, gaps, and extreme values affect the standard deviation.
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  • An interactive box plot applet that allows users to put in their own data that is part of a large collection of platform independent, interactive, java applets and activities for K-12 mathematics and teacher education.
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  • Song about the use of the Mann-Whitney U statistic (also known as the two sample Wilcoxon statistic). May be sung to the tune of "I Will Find You" by Peter Hammill; Fie Records, 1991. The audio was produced by Nicolas Acedo and sung by Jorge Baylon, both students in the University of Texas at El Paso Commercial Music Program.

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  • This text based website provides an explanation of some coincidences that are often discussed. It gives an explanation of the birthday problem along with a graphic display of the probability of birthday matches vs. the number of people included. It also discussess other popular coincidences such as the similarities between John F. Kennedy and Abraham Lincoln. It goes on to discuss steaks of heads and tails along with random features of stocks and the stock market prices.
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  • This lesson introduces two sample hypothesis testing for means and discusses the one-tailed and two-tailed t-tests.
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  • This applet draws one-dimensional Brownian motion. Click the mouse in the window to start zooming. Click again to stop. Since Brownian motion is self-similar in law, all of the zoomed pictures look the same.
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