Statistical Inference & Techniques

  • Big data analysis is explained in this online course that introduces the user to the tools Hadoop and Mapreduce. These tools allow for the parallel computing necessary to analyze large amounts of data.
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  • A short story that might be used as an out-of-class assignment to facilitate understanding the interpretation of a 95% confidence interval as a random interval that is expected to cover the true parameter in 95% of all samples. The story was written in 2011 by Canadian mathematician Robert Dawson from Saint Mary's University in Halifax Nova Scotia. The story was published as a two part series at www.Lablit.com
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  • A science fiction short story that could be used in an out-of-class assignment associated with the topic of cyclic trends in time series. The story was written in 1952 by American science fiction writer Robert Heinlein and published in Galaxy Science Fiction magazine.
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  • A joke that might be used in a discussion of the problem of using a simple linear regression to extrapolate beyond the range of the data (where it is unlikely that the linear relationship would continue to hold). The joke was written by Dennis Pearl from Penn State University.
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  • A cartoon to be used for discussing the selection of the best explanatory variable in a regression model. The cartoon was used in the March 2017 CAUSE Cartoon Caption Contest. The winning caption was submitted by Michele Balik-Meisner, a student at North Carolina State University. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. A second winning entry, by Michael Posner of Villanova University, may be found at www.causeweb.org/cause/resources/fun/cartoons/variable-wheel-ii Three honorable mentions that rose to the top of the judging in the March competition included “No no no! You randomize AFTER you select your research topic!” by Mickey Dunlap from University of Georgia; “This isn't what I meant by random variable!” by Larry Lesser from The University of Texas at El Paso; and “We find this method of finding 'significant' predictors to be quicker than using stepwise regression and it is even slightly more reproducible.” by Greg Snow from Brigham Young University.
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  • A cartoon to be used for discussing the selection of the best explanatory variable in a regression model. The cartoon was used in the March 2017 CAUSE Cartoon Caption Contest. The winning caption was submitted by Michael Posner, from Villanova University. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. A second winning entry, by Michele Balik-Meisner, a student at North Carolina State University, may be found at www.causeweb.org/cause/resources/fun/cartoons/variable-wheel-i Three honorable mentions that rose to the top of the judging in the March competition included “No no no! You randomize AFTER you select your research topic!” by Mickey Dunlap from University of Georgia; “This isn't what I meant by random variable!” by Larry Lesser from The University of Texas at El Paso; and “We find this method of finding 'significant' predictors to be quicker than using stepwise regression and it is even slightly more reproducible.” by Greg Snow from Brigham Young University.
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  • A cartoon to be used for discussing the affect on inference caused by subject-to-subject variability and how that relates to the differences between groups. The cartoon was used in the May 2017 CAUSE Cartoon Caption Contest. This caption was submitted by Larry Lesser from The University of Texas at El Paso and took honorable mention in the contest. The drawing was created by British cartoonist John Landers based on an idea from Dennis Pearl of Penn State University. The winning caption in the May competition may be found at www.causeweb.org/cause/resources/fun/cartoons/product-testing-i (written by Jim Alloway of EMSQ Associates) and an honorable mention may be found at www.causeweb.org/cause/resources/fun/cartoons/product-testing-iii written by John Bailer from Miami University.
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  • A song to aid in the discussion of the meaning and interpretation of p-values and type I errors. The song's lyrics were written in 2017 by Lawrence Lesser from The University of Texas at El Paso and may be sung to the tune of the 1977 Bee Gees Grammy winning hit "Stayin' Alive."
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  • This is a complete lesson module (including example problems with answers to selected problems) for the purpose of enabling students to: 1) Provide examples demonstrating how the margin of error, effect size, and variability of the outcome affect sample size computations. 2) Compute the sample size required to estimate population parameters with precision. 3) Interpret statistical power in tests of hypothesis. 4) Compute the sample size required to ensure high power when hypothesis testing.
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  • When performing a hypothesis test about the population mean, a possible reason for the failure of rejection of the null hypothesis is that there's an insufficient sample size to achieve a powerful test. Using a small data set, Minitab is used to check for normality of the data, to perform a 1-Sample t test, and to compute Power and Sample Size for 1-Sample t.
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