Univariate Distributions

  • How are earnings determined? Why do some people earn more than others? Does a better job necessarily mean a better salary? In this module, students will attempt to answer these questions and many others by examining factors such as education and occupation in terms of the role they play in determining earnings. Students will also look at the earnings of whites and compare them to the earnings of blacks, Latinos, and Asians. Another consideration will center on the effect of gender. Finally, students will turn their attention to the age of workers in terms what role it plays in determing earnings. Aside from earnings, students will also take a brief look at poverty with respect to the effect race-ethnicity and family structure has on creating and sustaining it.
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  • This module is designed to illustrate the effects of selection bias on the observed relationship between premarital cohabitation and later divorce. It also serves as a review of key methodological concepts introduced in the first part of the course.
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  • This collection of datasets covers many application areas, but are all for time series analysis. The data are in text format.
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  • This module provides an activity were students will attempt to explain how each of the following variables is related to child poverty within the United States: Race, Age, Family Type, Family Size, and Immigrant Status.
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  • This collection of datasets was compiled by the Biostatistics Department at Vanderbilt University. They come in R, S, Excel, and ASCII formats. Each also has a description in html format.
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  • This scatterplot lets users plot a number of demographic variables and see the log transformation of those variables for numerous countries and income groups. Users can also see the information for any year from 1975 to 2004.
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  • 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 simulates drawing samples from a binomial distribution. Users set the population proportion of success (pi), sample size (n), and number of samples. By clicking "Draw Samples," the applet will draw a sample and display the corresponding sample histogram. Each new sample drawn is added to the previous ones unless the user clicks "Reset" between samples. Users can choose to display the number and proportion of successes above or below a certain value (tail probabilities) by entering a value in the "Num Successes" box and clicking "Count." The portion of the distribution that meets the condition is highlighted in red, and the proportion of success is given at the bottom of the page. Clicking the inequality sign changes its direction. Clicking "Theo Values" displays the theoretical distribution in green on top of the empirical. Instructions and an activity for this applet can be found in the textbook "Investigating Statistical Concepts, Applications, and Methods" (ISCAM) in Lesson 3.2.2 on page 205.

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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 applet generates a histogram for two provided datasets, or by clicking "Edit Data", users can input their own data. Users can also manipulate the axes and bin width.
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