Significance Testing Principles

  • The goal of this assignment is to obtain summary statistics for the variables in the data set, ncbirth1450.xls, which represents a random sample of 1450 births from the state of North Carolina.
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  • This assignment has students investigate whether the risk of having a child with a low birth weight is higher when the mother drinks and smokes during pregnancy. The data set represents a random sample of 1450 births from the state of North Carolina.
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  • The assignment begins with creating a summary of and tables for the data, then walks the student through the steps of creating a hypothesis testing report. It uses the data set ncbirth200.xls, which is a random sample of 200 births from the data set ncbirth1450.xls.
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  • This webpage shows a grading rubric for group projects.
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  • This 21 page pdf file includes teaching tips for using projects when teaching statistics such as group formation and grading rubrics. This site provides sample projects on data and probability summaries, hypothesis testing and simple linear regression.
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  • This collection of free, interactive Java applets provides a graphical interface for studying the power of the most commonly encountered experimental designs. Intended to be useful in planning statistical studies, these applets cover confidence intervals for means or proportions, one and two sample hypothesis tests for means or proportions, linear regression, balanced ANOVA designs, and tests of multiple correlation, Chi-square, and Poisson. Each applet opens in its own window with sliders, which are convertible to number-entry fields, for manipulating associated parameters. Controlling for the other parameters, users can change sample size, standard deviation, type I error (alpha) and effect size one at a time to see how each affects power. Conversely, users can manipulate the power for the test to determine the necessary sample size or margin of error. Additional features include a graph option by which the program plots a dependent variable (i.e. power) over a range of parameter values; the graph is automatically updated as the parameters are changed. Each dialog window also offers a Help menu which provides instructions for using the applet. The applets can be used over the Internet or downloaded onto the user's own computer.
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  • This set of pages describes software the author wrote to implement bootstrap and resampling procedures. It also contains an introduction to resampling and the bootstrap; and examples applying these procedures to the mean, the median, correlation between two groups, and analysis of variance.
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  • This journal article is a summary of resampling methods such as the jackknife, bootstrap, and permutation tests. It summarizes the tests, describes various software to perform the tests, and has a list of references.
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  • This journal article gives examples of erroneous beliefs about probability. It specifically examines the belief that a random sample must be representative of the true population.
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  • This applet allows the user to enter data, then returns the values of empirical cumulative distribution function by sorting the data and reporting the height of the curve at each point. It does not show the graph.

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