MATH-240 Applied Statistical Methods
Fall for 2017-2018
Spring for 2017-2018
This course is an introduction to the real world of statistics and data analysis. We will explore real data sets, apply linear regression models to the data, conduct model inference, assess the validity of model assumptions, and determine which conclusions we can make. The course begins with review of exploratory data analysis, informal techniques for summarizing and viewing data, and principles of statistical inference. We then consider simple linear regression, a model that uses only one predictor. After briefly reviewing some matrix algebra, we turn to multiple linear regression, a model that uses multiple variables to predict the response of interest. Model diagnostics and model selection will be thoroughly covered. The course continues with one-way and multi-factor ANOVA, and time permitting, basic categorical data analysis. Classroom material will be accompanied by hands-on experience using the statistical software R.
Credits: 3
Prerequisites: Math-140 or Math-040
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