STAT 302/604, Analysis of Observational and Experimental Data
Introduction
This book will contain course material and examples related to STAT 302.
The description of this course states:
The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in observational and experimental studies.
This course also has the following prerequisites:
One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, with a minimum grade of C-.
This course will be quantitative and will involve exploring statistical methods which can be used to analyse data you may collect (for example, in an honors thesis).
After taking this course, you should have a understanding of several commonly used techniques for analysing data. In particular, you should be aware of what methods will be suitable for a certain problem (and what won’t be).
As this is an applied statistics course focusing on analysing data, statistical computing will be incorporated throughout. If you do not have previous computing experience that is ok, an introduction will be provided here. We will use the programming language R. This will be examined in homeworks, where you will have to use code you have seen in class to fit methods we study to some data.
You will not be expected to write any code or pseudo code in an exam. However, you will be expected to analyse the output of some code, which is something we will do throughout the class and the homeworks.
Syllabus
- Review of statistical concepts, inference
- Simple linear regression
- Multiple linear regression
- Analysis of Variance (ANOVA)