Statistical Modeling, Courtney Brown, Emory University
Summary: This is a course in statistics as they are applied in the social sciences. The first half of the course involves simple descriptive statistics, t-tests, and the chi-squared statistic, all of which are applied using the SAS statistical software. The second half of the course addresses bivariate regression, multiple regression, and logistic regression.
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- Artist: Courtney Brown, Ph.D.
- Copyright: ℗ & © 2007 Courtney Brown
Podcasts:
Statistical Modeling: Assignment 1 with R, Courtney Brown, Emory University
Statistical Modeling: Multiple Regression and Multicollinearity, Courtney Brown, Emory University
Statistical Modeling: Working with the Democracy Data Set and Multiple Regression, Courtney Brown, Emory University
Statistical Modeling: Intercept and Slope Dummy Variables, Courtney Brown, Emory University
Statistical Modeling: Multivariate Relationships, Courtney Brown, Emory University
Statistical Modeling: Second draft of final project, plus multiple regression, Courtney Brown, Emory University
Statistical Modeling: First draft of final project, plus bivariate regression, Courtney Brown, Emory University
Statistical Modeling: Midterm Problem Review, Courtney Brown, Emory University
Statistical Modeling: Contingency tables and the chi-squared statistic, Courtney Brown, Emory University
Statistical Modeling: Type I and Type II Errors, Plus Testing the Difference Between Means, Courtney Brown, Emory University
Statistical Modeling: Assignment #2, Courtney Brown, Emory University
Statistical Modeling: Confidence Intervals, Courtney Brown, Emory University
Statistical Modeling: The Normal Distribution, z-scores, and Beginning Statistical Inference, Courtney Brown, Emory University
Statistical Modeling: Assignment #1, Courtney Brown, Emory University
Statistical Modeling: Distributions, Measures of Central Tendency, and Measures of Distribution, Courtney Brown, Emory University
