Data Analysis II

Data Analysis II takes an applied approach to statistical analysis and research methodology and is the second in a two-course sequence. Provides students with statistical background, conceptual understanding, technical writing skills, computer application, and the ability to apply these skills to realistic data analysis problems and research designs. Topics include simple regression and correlation, multiple regression, and logistic regression. The laboratory (USP654L) must be taken concurrently. Recommended prerequisites: USP 534/634 or an equivalent course approved by the instructor and prior experience with statistical software.


Course info
When Mon 4:00 - 7:30pm
Where Remote via Zoom (link on D2L)
Office Hours Mon 2 - 3:45pm & by appointment

Instructor
Instructor Liming Wang  

Texts
Regression Analysis for the Social Sciences Gordon, Rachel Routledge, 2015
R for Data Science Grolemund, Wickham O'Reilly, 1st edition, 2017

We will read a few chapters in Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences 3rd edition by Cohen et al from Routledge as supplement.

Additional readings will be posted to D2L/Readings

Software

This course will use the R statistical software. R is free and available for download at http://cran.r-project.org. We will use RStudio (https://www.rstudio.com/) as our main interface to R. R and RStudio is installed on the lab computers across the campus. Labs will be offered weekly to assist in using R to complete the assignments and R examples will be used during regular sessions. I can provide additional assistance with the software. DataQuest is a good resource to learn R along with data analysis skills.

It is possible to use your choice of other stats software, such as SAS, SPSS, or Stata, for this class; I do encourage you to continue using one of these software if you are already using it. It is also a good idea to ask your graduate adviser and/or GRA supervisor which software would be most useful for you, and use it. If you plan to use one of these software, I will provide as much assistance as I can.

Hardware

Class meets virutally via Zoom; you are welcome to bring and use your own laptop (Windows, Mac, or Linux). Check out the Tools and Datasets section for instructions of installing necessary software on your own computer.

Attributions