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  • This applet is designed to teach an application of probability. This java applet works by simulating a situation where a three stage rocket is about to be launched. In order for a successful launch to occur all three stages of the rocket must successfully pass their pre-takeoff tests. By default, each stage has a 50% chance of success, however, this can be altered by dragging the bar next to each stage.
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  • In this applet, we simulate a series of hypothesis of tests for the value of the parameter p in a Bernoulli random variable. Each column of red and green marks represents a sample of 30 observations. "Successes'' are coded by green marks and "failures'' by red marks.
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  • This applet simulates rolling dice to illustrate the central limit theorem. The user can choose between 1, 2, 6, or 9 dice to roll 1, 5, 20, or 100 times. The distribution is graphically displayed. This applet needs to be resized for optimal viewing.
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  • This activity allows the user to simulate pulling red and green balls out of three boxes. The boxes are pre-arranged so that there are two red balls in one box, two green balls in another, and one green and one red ball in the third. The user can shuffle the order of the boxes and the order of the balls in the boxes. To run in single trial mode, click on one of the box to see if the first ball is green. If it is, click on the box again to see if the second ball is green also. A count will be kept of the results. To run in multiple trial mode, enter the number of trials desired in the box and click on the run multiple trials button. This activity would work well in groups of two to three for about twenty minutes if you use the exploration questions provided and ten minutes otherwise.
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  • Gives an overview of variables, classifications, measurements, relations, and other basic statistical concepts. Also contains two animated graphs.
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  • 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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  • This chapter of the HyperStat Online Textbook discusses in detail sampling distributions of various statistics (mean, median, proportions, correlation, etc.), differences between such statistics, the Central Limit Theorem, and standard error, giving formulas, examples, and exercises.
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  • This site has a wide collection of statistical objects inluding an online textbook covering first-year non-calculus based statistics (e.g. Normal distribution, ANOVA, Chi-Square). There is a simulation/demonstration section containing Java Applets on these first-year topics (ANOVA, Binomial Distribution,Central Limit Theorem, Chi Square, Confidence Interval, Correlation, Central Tendency, Effect Size, Goodness of Fit, Histogram, Normal Distribution, Power, Regression, Repeated Measures, Restriction of Range, Sampling Distribution, Skew, t-test, Transformations). Additionally, this page contains links for 10 case studies covering the topics in the first-year statistics course. There is also a page with some basic statistical analysis tools that will aid in doing the computations.
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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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