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Georgetown University

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Detailed Course Information

 

Fall 2017
Oct 19, 2017
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MATH 240 - Applied Statistical Methods
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. 

3.000 Credit hours
3.000 Lecture hours
0.000 Lab hours

Levels: Undergraduate
Schedule Types: Lecture

Mathematics Department

Course Attributes:
SFS/IECO Supporting Courses, College/Bus Admin Minor Bridge

Prerequisites:
MATH 140 or MATH 040 or MATH 04- or ECON 121 or OPIM 173

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