Statistical Inference & Techniques

  • 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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  • Compared to probability calculators, the traditional format of distribution tables has the advantage of showing many values simultaneously and, thus, enables the user to examine and quickly explore ranges of probabilities. This webpage includes a list of distributions and tables, including the standard normal (Z) table, student's t table, chi-square table, and F distribution tables. An animation of the density function and distribution function is shown above each distribution table to demonstrate the effects changing degrees of freedom and significance levels have on the shape of a distribution.

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  • This site contains 100 modules designed to introduce concepts in statistics. The modules are divided into categories such as Descriptive Statistics, Inferential Statistics, Related Measures, Enumeration Statistics, and ANOVA. Click the green button on the side to start the modules, then click "Main Menu" at the top to see a list of topics. Topics include Describing Numbers, Normal Curve, Sampling Distributions, Hypothesis Testing, Regression, and Chi-Square. The site also includes a glossary, statistical tables and simulations, and a personalized progress report. Key Words: Collection; Central Tendency; Spread; Correlation.
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  • Legal proceedings are like statistics. If you manipulate them, you can prove anything. A quote by Bristish-born Canadian novelist Arthur Hailey (1920 - 2004). The quote is found in the novel "Airpot" (1968; Doubleday, p. 385). The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.
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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 logarithmic transformation in statistics. May be sung to the tune of "Hound Dog" which was popularized by Elvis Presley. Lyrics written by Dennis Pearl with assistance from Deb Rumsey. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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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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