College --Undergrad Upper Division

  • This graduate level course offers an introduction into regression analysis. A researcher is often interested in using sample data to investigate relationships, with an ultimate goal of creating a model to predict a future value for some dependent variable. The process of finding this mathematical model that best fits the data involves regression analysis.  STAT 501 is an applied linear regression course that emphasizes data analysis and interpretation and is perfect for both students and teachers of statistics courses.

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  • Correspondence analysis is a method allowing you to describe synthetically a contingency table in which homogeneous individuals are classified on two criterias (or categorical variables, continuous ones being usable if discretized).  This resource tells how it can be used, graphical representations of this process, and gives examples of it in action. 

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  • A song to be used in discussing the value of random selection in sampling and random assignment in experimentation. The lyrics were written by Mary McLellan from Aledo High School in Aledo, Texas as one of several dozen songs created for her AP statistics course. The song may be sung to the tune of the 2014 hit “All About that Bass,” by Meghan Trainor. Also, an accompanying video may be found at https://www.youtube.com/watch?v=br-5FtoYfkc

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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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  • Document (pdf) illustrating a test of normality using an Anderson-Darling test in MINITAB and a test of equality of variances with an F-test in EXCEL.
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  • Powerpoint explaining what power is and how power and sample size are related to one another.
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  • A resource providing information about what the sample size is, what factors the sample size depends on, and how it can be determined,
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  • Resource providing information about: computation of the sample size and the assumptions that must be made to do so. Several examples are given with different conditions in each, and a table showing minimum sample sizes for a two-sided test.
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  • Article that explains why comparing statistical significance, sample size and expected effects are important before constructing and experiment.
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