Laboratories

  • This tutorial introduces 9 sources of threat to internal vailidity and asks the user to classify hypothetical experiments as either internally valid or invalid and identify the source of threat if invalid.
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  • The t-distribution activity is a student-based in-class activity to illustrate the conceptual reason for the t-distribution. Students use TI-83/84 calculators to conduct a simulation of random samples. The students calculate standard scores with both the population standard deviation and the sample standard deviation. The resulting values are pooled over the entire class to give the simulation a reasonable number of iterations.
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  • This PowerPoint presentation teaches sampling distributions related to proportions and means using multiple examples, charts, and graphs.
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  • This page will perform a two-way factorial analysis of variance for designs in which there are 2-4 levels of each of two variables, A and B, with each subject measured under each of the AxB combinations.

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  • This page will perform a two-way factorial analysis of variance for designs in which there are 2-4 randomized blocks of matched subjects, with 2-4 repeated measures for each subject.

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  • This page will compute the Two-Way Factorial ANOVA for Independent Samples, for up to four rows by four columns. This page will also calculate the critical values of Tukey's HSD for purposes of post-ANOVA comparisons.

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  • The following pages calculate r, r-squared, regression constants, Y residuals, and standard error of estimate for a set of N bivariate values of X and Y, and perform a t-test for the significance of the obtained value of r. Allows for import of raw data from a spreadsheet; for samples of any size, large or small.

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  • This page will calculate r_s , the Spearman rank- order correlation coefficient, for a bivariate set of paired XY rankings. As the page opens, you will be prompted to enter the number of items for which there are paired rankings. If you are starting out with raw (unranked) data, the necessary rank-ordering will be performed automatically.

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  • For n = 50 to 400, in steps of size 5, this program computes and displays (1) the exact probability P(|A_n - p| >= epsilon), where A_n is the average outcome of n Bernoulli trials with probability p of success, and (2) the Chebyshev estimate p(1-p)/(n(epsilon^2)) for this probability. You can specify p and epsilon.
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  • These lecture notes are composed of nearly 180 PowerPoint slides that have been coverted to a pdf file (6 per page) on Biomedical Imaging. The following topics are outlined: Vocabulary, Displaying Data, Central Tendency and Variability, Normal Z-scores, Standardized Distribution, Probability, Samples & Sampling Error, Type I and Type II Errors, Power of a Test, Hypothesis Testing, One Sample Tests, Two Independent Sample Tests, Two Dependent Sample Tests & Estimation, Correlation and Regression Techniques, Non-Parametric Statistical Tests, Applications of Central Limit Theorem, Law of Large Numbers, Design of Studies and Experiments, Fisher's F-Test, Analysis Of Variance(ANOVA), Principle Component Analysis (PCA), Chi-Square Goodness-of-fit test, Multiple Linear Regression, General Linear Model, Bootstrapping and Resampling.
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