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Categorical versus Quantitative

  • This applet allows users to run experiments such as Ball and Urn, Buffon's Needle, Craps, Monty Hall, and many more. Select an experiment from the drop down menu and click "About" to read its description. Then, set the parameter values. Set the sample size using the "Update" box and the number of samples using the "Stop" box. The single arrow button takes one sample and the double arrow button takes the number of samples selected. Graphs of the theoretical and empirical distributions are shown. Requires JAVA
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  • This applet allows users to play several probability games like Monty Hall, Gambler's Ruin, Galton's Board, etc. Select a game from the drop down menu and click "About" to read its background. Users can manipulate the parameters for each game. Graphs of the theoretical and empirical distributions are shown. Requires JAVA.
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  • This website is compilation of data from sources such as the CIA World Factbook, UN, and OECD. You can generate maps and graphs to statistically compare and research Nations.

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  • This section of an online textbook discusses the correlation coefficient and illustrated it visually through graphs. It explains calculations as well as how scatter plots can describe data. It covers significance tests for relationships, the Spearman rank correlation and the regression equation. Exercises and answers are included.
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  • Survival analysis is concerned with studying the time between entry to a study and a subsequent event. This site looks at the Kaplan-Meier survival curve, its method and how to calculate it. It provides exercises as well as answers.
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  • The dataset presented in this article contains information on respiratory function and smoking. The data can be used to explore descriptive statistics, graphical analysis, regression, and observational studies. The data are in .dat format.
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  • This article describes a dataset on body temperature, gender, and heart rate. It addresses concepts like true means, confidence intervals, t-statistics, t-tests, the normal distribution, and regression.
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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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  • In these activities designed to introduce sampling distributions and the Central Limit Theorem, students generate several small samples and note patterns in the distributions of the means and proportions that they themselves calculate from these samples. Outside of class, students generate samples of dice rolls and coin spins and draw random samples from small populations for which data is given on each individual. Students report their sample means and proportions to the instructor who then compiles the results into a single data file for in-class exploration of sampling distributions and the Central Limit Theorem. Key words: Sampling distribution, sample mean, sample proportion, central limit theorem

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  • 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), that not all histograms are easy to classify, that there is a difference between models (normal, uniform) and characteristics (skewness, symmetry, etc.). Key words: Histogram, shape, normal, uniform, skewed, symmetric, bimodal
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