Statistical Inference & Techniques

  • This collection of calculators allows users to perform a number of statistical applications. Each provides background on the procedure and an example. Users can compute Descriptive Statistics and perform t-tests, Chi-square tests, Kolmogorov-Smirnov tests, Fisher's Exact Test, contingency tables, ANOVA, and regression.

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  • This applet performs a hypothesis test for the mean of a single normal population, variance known. Users set the hypothesized mean, true mean, variance, and appropriate alternative hypothesis. The applet plots a representative distribution under the given values with power shaded in blue and significance level shaded in red.
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  • The 29-item attitudinal scale consists of two subscales: attitude toward the field of statistics (20 items) and attitude toward the course (9 items). Students are asked to respond to how they currently feel about a statement (i.e., "I feel that statistics will be useful to me in my profession") using a 1 (strongly disagree) to 5 (strongly agree) response scale.
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  • This Compendium describes distributions appropriate for the modeling of random data. The number of distributions (56) is large, including: 1. Continuous distributions (30), (Symmetric (11) and Skewed (19)) 2. Continuous binary mixtures(17), 3. Discrete distributions (5), 4. Discrete binary mixtures (4), All formulas are shown in their fully-parametrized form, not the standard form. Many of the formulas given are seldom described. Random variate generation is included where feasible.
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  • This site discusses types of data, stem and leaf plots, mean and median, histograms, and barcharts. Exercises are also provided, as well as their corresponding answers.
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  • This short article discusses the difference between "important" and "statistically significant." The data used come from a study comparing male faculty salaries to female faculty salaries.
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  • This exercise includes a discussion on comparing data with very different sample sizes and nonhomogeneity of variance. The data comes from a study on the behavior of pregnant women with regard to cigarette smoking.
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  • This lesson describes bootstrapping in the context of a statistics class for psychology students.
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  • This excerpt from Engineering Statistics Handbook gives a definition for and examples of outliers. A sub-page also discusses Grubbs' Test for Outliers
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  • This text document lists detailed learning objectives for introductory statistics courses. Learning objectives are brief, clear statements of what learners will be able to perform at the end of a course. These objectives were developed for a one semester general education introductory statistics course. The objectives cover the broad categories of Graphics, Summary Statistics, The Normal Distribution, Correlation and Scatterplots, Introduction to Regression, Two way Tables, Data Collection and Surveys, Basic Probability, Sampling Distributions, Confidence Intervals, Tests of Hypothesis, and T-distributions.
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