Workshops for Fall, 2019
Introduction to R, Thursday, October 10 from 9 a.m. to 12 noon in the Visualization Portal, Math Sciences 5628
Description: R is a programming environment that runs on Windows, Macintosh and UNIX platforms. This class is designed for people who are just starting to use R. The students in the class will have a hands-on experience using R for doing statistics, graphics, and data management. The class notes are the scripts for the class. The R class notes do not contain any of the computer output. The class notes are not meant to be an R textbook or a reference manual. However, it is possible for individuals to use the class notes to help them learn R even if they don’t enroll in the class. Students should bring their own laptop computers with R 3.6.1 (https://cran.r-project.org/ ) installed. Installation of R-Studio (https://www.rstudio.com/products/rstudio/download/ ) is also strongly recommended. workshop notes sign-up link
Introduction to SAS, Thursday, October 17 from 9 a.m. to 12 noon in the Visualization Portal, Math Sciences 5628
Description: SAS is a powerful statistical package that runs on many platforms, including Windows and Unix. This class is designed for people who are just getting started using SAS. The students in the class will have a hands-on experience using SAS for statistics, graphics, and data management. The SAS class notes do not contain any of the computer output. The class notes are not meant to be a SAS textbook or a reference manual. However, it is possible for individuals to use the class notes to help in learning SAS even if they don’t enroll in the classes. Students should bring their own laptop computers with SAS installed. SAS can be purchased from the computer store in the book store in Ackerman, or students can download SAS University Edition (https://www.sas.com/en_us/software/university-edition.html ), which is free. workshop notes sign-up link
Introduction to Stata, Tuesday, October 22 from 1 to 4 p.m. in CLICC Classroom A (third floor of the Powell Library building)
Description: Stata is a powerful and yet easy-to-use statistical package that runs on Windows, Macintosh and Unix platforms. This class is designed for people who are just getting started using Stata. The students in the class will have a hands-on experience using Stata for statistics, graphics and data management. The class notes are the scripts for the class available to the students in the class and to others on the Internet. The Stata class notes do not contain any of the output. The class notes are not meant to be a Stata textbook or a reference manual. However, it is possible for individuals to use the class notes to help in learning Stata even if they don’t enroll in the class. Computers with Stata installed will be available to attendees. workshop notes sign-up link
Introduction to SPSS, Thursday, October 24 from 9 a.m. to 12 noon in YRL Research Commons Classroom (Room 11630F)
Description: SPSS is a very easy-to-use statistical package that runs on Windows, Macintosh and UNIX platforms. This class is designed for people who are just starting to use SPSS. The students in the class will have a hands-on experience using SPSS for doing statistics, graphics, and data management. The class notes are the scripts for the class. The SPSS class notes do not contain any of the computer output. The class notes are not meant to be an SPSS textbook or a reference manual. However, it is possible for individuals to use the class notes to help them learn SPSS even if they don’t enroll in the class. These notes were developed using SPSS version 22, but most of the material should work with earlier or later versions of SPSS. Computers with SPSS installed will be available to attendees. workshop notes sign-up link
Introduction to R, Monday, November 18 from 1 to 4 p.m. in the Visualization Portal, Math Sciences 5628
Description: R is a programming environment that runs on Windows, Macintosh and UNIX platforms. This class is designed for people who are just starting to use R. The students in the class will have a hands-on experience using R for doing statistics, graphics, and data management. The class notes are the scripts for the class. The R class notes do not contain any of the computer output. The class notes are not meant to be an R textbook or a reference manual. However, it is possible for individuals to use the class notes to help them learn R even if they don’t enroll in the class. Students should bring their own laptop computers with R 3.6.1 (https://cran.r-project.org/ ) installed. Installation of R-Studio (https://www.rstudio.com/products/rstudio/download/ ) is also strongly recommended. workshop notes
sign-up link
Past Classes and Workshops Available Online
- Introduction to Stata 15
- Stata Data Management
- Regression with Stata
- Logistic Regression with Stata
- Beyond Binary Logistic Regression with Stata
- Multiple Imputation in Stata 15
- Introduction to Survey Data Analysis
- Applied Survey Data Analysis
- Survival Analysis Using Stata
- Introduction to Meta-analysis using Stata
- Introduction to Programming in Stata
- Introduction to SAS 9.4
- Programming Basics in SAS 9.4
- Analyzing and Visualizing Interactions in SAS 9.4
- Regression with SAS
- Logistic Regression in SAS
- Repeated Measures Analysis in SAS
- Applied Survey Data Analysis using SAS 9.4
- Multiple Imputation in SAS 9.4
- Survival Analysis Using SAS
- Using Arrays in SAS
- Introduction to SAS Macro Language
- Introduction to SPSS (point-and-click and syntax)
- Introduction to Regression with SPSS (Version 23)
- A Practical Introduction to Factor Analysis
- Principal Components (PCA) and Exploratory Factor Analysis (EFA) with SPSS
- Introduction to SPSS Syntax, Part1 (using SPSS version 21)
- Introduction to SPSS Syntax, Part 2 (using SPSS version 21)
- Repeated Measures Analysis in SPSS
- Using the SPSS Mixed Command
- Graphics using SPSS
Mplus and Latent Variable Analysis
- Introduction to R
- R Markdown Basics
- Introduction to ggplot2
- R Data Management
- Repeated Measures Analysis in R
- Introduction to Regression in R
- Decomposing, Probing and Plotting Interactions in R
Longitudinal Data Analysis
- Longitudinal Research: Present Status and Future Prospects by Judith Singer & John Willett
- Analyzing Longitudinal Data using Multilevel Modeling
Power Analysis
- Deciphering Interactions in Logistic Regression
- Regression Models with Count Data
- Statistical Writing
Other