In this module, students will become familiar with population standardized regression methods when working with data that is expressed as per-capita rates

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In this module, students will become familiar with logistic (Binomial) regression for data that either consists of 1’s and 0’s (“yes” and “no”), or fractions that represent the number of successes out of n trials.  We focus on the R glm() method for logistic linear regression. Continue reading →

 In this module, students will become familiar with Poisson regression for count data.  We focus on the R glm() method for linear regression, and then describe the R optim() method that can be used for non-linear models. Continue reading →

In this module we will discuss how to conduct one-sample and two-sample Students t-tests of sample means when the variance of the sample is unknown, testing the equality of the means of several samples, and z-test of sample means when the variance is known.

Contents:

• Students t-test of the mean of one sample
• Example of Students t-test of the mean of one sample
• Students t-test comparing the means of two samples
• Example of Students t-test comparing the means of two samples
• Limitations of the Students t-test
• Testing for equality of more than two means (ANOVA)
• One and two sample Z-tests

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