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*Research Data Services @ Georgia State University Library: WORKSHOPS ~ Data Analysis Tools ~ Quantitative (Stata, SPSS, SAS, R, Python) & Qualitative (NVivo)

WORKSHOPS ~ DATA ANALYSIS TOOLS

R Workshop Series


R Workshop Series

Get GSU Data Ready! Badge Micro-Credentials for completing these workshops to show others your commitment to learning data skills! Learn more at lib.gsu.edu/data-ready


The R workshop series will introduce participants to the fundamentals of using the R programming language and associated tools for the purposes of performing common data analysis tasks. The R programming language is 100% free to use and is extremely popular amongst researchers in both academia, business, and non-profits. It is especially useful for conducting statistical analysis.

This series consists of four workshops. Individuals are encouraged to attend (or watch the recording) for the “R 1: Getting Started…” workshop first; especially for individuals who are brand new to using R. The content for the remaining workshops are independent of each other and can be attended in any order.

While these workshops are taught exclusively using code (i.e. there are no point-and-click methods), attendees do not need to have any prior experience with programming, coding, or scripting. All are welcome.

Skill Requirements: None.

Software Requirements for Hands-on Participation:

For participants wishing to follow along with the “hands-on” portion of the workshop, please see the directions at the following url: https://research.library.gsu.edu/R/workshop


R 1: Getting Started with R and RStudio

Workshop Topics:

  • Using RStudio to work with R
  • R syntax, commands, functions, and packages
  • Opening, viewing, and exploring data
  • Generating basic descriptive statistics from data


R 2: Tidyverse and Manipulating Data

Workshop Topics:

  • Introduction to Tidyverse packages (emphasis on dplyr)
  • Transforming and generating variables
  • Handling data with missing values
  • “Piping” data and data processes

R 3: Data Visualization and Mapping

Workshop Topics:

  • Creating statistical plots using ggplot2
  • Customizing plot colors, themes, labels, etc…
  • Working with GIS data to create maps
  • Modifying maps with overlays, custom aesthetics, and additional data

R 4: Statistical Modelling

Workshop Topics:

  • Basic analysis, descriptive statistics, t-tests
  • Creating linear models (multiple linear regression & logistic regression)
  • Evaluating linear models and generating predictions
  • Creating simple machine learning models (Time permitting)

SAS Workshop Series


SAS Workshop Series

Get a GSU Data Ready! Badge Micro-Credential for completing these workshops to show others your commitment to learning data skills! Learn more at lib.gsu.edu/data-ready


This workshop series completes all analysis using code. No previous knowledge of coding is required. This series is for the Windows version of SAS.


SAS 1: SAS Basics

This is the first SAS workshop in a two-part series. This interactive workshop will introduce users to the SAS system. Applied, hands on, examples using real data will be used. NOTE: This workshop is aimed at people who do not have experience using the SAS system. Those who have used SAS in the past may find this workshop too foundational and are encouraged to attend our forthcoming advanced SAS sessions.

Workshop Topics:

  • Reading data into SAS
  • Conducting basic data cleaning and recoding
  • Using basic SAS procedures (e.g., PROC CONTENTS, PROC PRINT, PROC FREQ) to view and understand data.
  • PROC FREQ, PROC UNIVARIATE, and PROC MEANS will be demonstrated to complete basic descriptive statistics.
  • An introduction to bivariate statistics in SAS.

Prerequisites: No prior experience with SAS is required. Basic understanding of univariate and bivariate statistics is helpful but not required.


SAS 2: Data Analysis

This is the second SAS workshop in a two-part series. In this interactive workshop, SAS users will go beyond the basics to develop comfort with more advanced statistical analyses using the SAS system. Applied, hands on, examples using real data will be used. NOTE: Basic knowledge of the SAS system will be helpful for those who want to participate in the applied portion of the workshop.

Workshop Topics:

  • Conducting bivariate and multivariable analyses using SAS procedures like PROC FREQ, PROC TTEST, PROC ANOVA, PROC GLM, PROC LOGISTIC, and PROC REG.
  • Best practices for checking statistical assumptions, selecting appropriate statistical procedures, and reporting and visualizing results will be discussed.

Prerequisites: Basic knowledge of the SAS system will be helpful for those who want to participate in the applied portion of the workshop. Basic understanding of bivariate and multivariable statistics is helpful.

SPSS Workshop Series


SPSS Workshop Series

Get a GSU Data Ready! Badge Micro-Credential for completing these workshops to show others your commitment to learning data skills! Learn more at lib.gsu.edu/data-ready


The SPSS 1 and SPSS 2 workshops in this two-part series focus on using the point-and-click method for using SPSS; the syntax/code method is introduced briefly.


SPSS 1: Getting Started

This workshop is the first of a two-part series on SPSS, a statistical software package that is widely used by scientists throughout the social sciences for analysis of quantitative data.

Please note: This workshop focuses on using the point-and-click method for using SPSS; the syntax/code method is introduced briefly.

Workshop Topics

  • Navigating SPSS
  • Entering and importing data from different formats (such as text and Excel files)
  • Defining variables (defining and labeling codes, selecting appropriate levels of measurement)
  • Manipulating and transforming data (selecting cases and splitting files; recoding and computing variables)
  • Running descriptive statistics
  • Generating simple graphs

Prerequisites: None.


SPSS 2: Analyzing Data

This workshop is the second of a two-part series on SPSS, a statistical software package that is widely used by scientists throughout the social sciences for analysis of quantitative data.

Please note: This workshop focuses on using the point-and-click method for using SPSS; the syntax/code method is introduced briefly.

Workshop Topics

  • Cross-tabulation and Chi-Square tests
  • Analysis of Variance (ANOVA)
  • T-tests
  • Correlation analysis
  • Multiple regression analysis

Prerequisites: Attendance at SPSS 1 preferred, or completion of Parts 1-6 of the Lynda.com "SPSS Statistics Essential Training" tutorial.

NVivo Workshop Series


NVivo Workshop Series

Get a GSU Data Ready! Badge Micro-Credential for completing these workshops to show others your commitment to learning data skills! Learn more at lib.gsu.edu/data-ready


This workshop is for the *WINDOWS* version of NVivo. The Mac version differs significantly from the Windows; consequently, attending the Windows workshop if you will be using the Mac version is not recommended. We do not offer workshops on the Mac version due to having no Mac labs to do so. If you need one-on-one training for the Mac version of NVivo, please directly contact Mandy Swygart-Hobaugh, Ph.D. See the NVivo research guide here.


NVivo 1 for Windows: Getting Started

This is the first workshop in a two-part series on NVivo qualitative data analysis software.

Workshop Topics

  • Getting to know the NVivo workspace
  • Exploring different types of data types/files that can be analyzed
  • Basic coding of text-based files
  • Using Queries and Automated features to explore and code your data
  • Recording comments and ideas

Prerequisites: Basic understanding of qualitative research methods is suggested, but not required. Watching this short tutorial on coding qualitative data before attending the workshop is recommended.


NVivo 2 for Windows: Exploring Your Data

This is the second workshop in a two-part series on NVivo qualitative data analysis software.

Workshop Topics

  • Creating Classifications with Attribute Values to facilitate comparative analyses
  • Crosstab and Matrix Coding queries
  • Data visualizations
  • Sharing findings with Reports and exporting Codebooks

Prerequisites: NVivo 1

Stata Workshop Series


Stata Workshop Series

Get a GSU Data Ready! Badge Micro-Credential for completing these workshops to show others your commitment to learning data skills! Learn more at lib.gsu.edu/data-ready


  • LIVE workshops are no longer offered for this series.
  • For RECORDED workshops: Click here.
  • For ONLINE GUIDE: Click here.

This workshop series completes all analysis using code. No previous knowledge of coding is required. This series is for the Windows version of Stata. See the Stata research guide here.


Stata 1: Introduction to Stata

This workshop is the first of a three-part series on Stata. Stata is a statistical software package. Stata is widely used by scientists throughout the social sciences for analysis of quantitative data ranging from simple descriptive analysis to complex statistical modeling.

Please note: This workshop completes all analysis using code. No previous knowledge of coding is required.

Workshop Topics:

  • Opening data
  • Generating variables (basic)
  • Frequency distributions
  • Analysis: summary statistics

Prerequisites: None.


Stata 2: Basic Data Analysis

This workshop is the second in a three-part series on Stata. Stata is a statistical software package. Stata is widely used by scientists throughout the social sciences for analysis of quantitative data ranging from simple descriptive analysis to complex statistical modeling.

Please note: This workshop completes all analysis using code. No previous knowledge of coding is required.

Workshop Topics:

  • Generating variables (advanced)
  • Analysis: Chi-square, ANOVA, regression
  • Graphs
  • Navigating help features

Prerequisites: Stata 1 or basic knowledge of Stata.


Stata 3: Advanced Data Analysis

This workshop is the third in a three-part series on Stata. Stata is a statistical software package. Stata is widely used by scientists throughout the social sciences for analysis of quantitative data ranging from simple descriptive analysis to complex statistical modeling.

Please note: This workshop completes all analysis using code. No previous knowledge of coding is required.

Workshop Topics:

  • Troubleshooting code
  • Generating scales
  • 3, 4, and 5 way cross tabulations

Prerequisites: Stata 1 and Stata 2 or moderate knowledge of Stata.

Python & Data Workshop Series


Python & Data Workshop Series

Get a GSU Data Ready! Badge Micro-Credential for completing these workshops to show others your commitment to learning data skills! Learn more at lib.gsu.edu/data-ready


  • LIVE workshops are no longer offered for this series.
  • For RECORDED workshops: Click here.
  • For ONLINE GUIDE: Click here.

The Python & Data workshop series will introduce participants to the fundamentals of using the Python programming language and associated tools for the purposes of performing common data analysis tasks. Python is an extremely popular programming language used by analysts, researchers, and scientists in many different disciplines.

This series consists of three workshops. For individuals who are new to Python, coding, or data analysis, it is highly recommended that the workshops be attended in sequential order. Additionally, while these workshops are taught exclusively using code (i.e. there are no point-and-click methods), attendees do not need to have any prior experience with programming, coding, or scripting. All are welcome.

Skill Requirements: None.

Software Requirements for Hands-on Participation:

  • Participants will need a Google / Gmail account in order to access Google Colab
  • No software installation is required.

Python & Data 0: Google Colab

This video-only recorded workshop provides a short, high-level overview of Google Colab and how it relates to the other Python workshops. There is no live version of this workshop; it is solely available as a recorded version on our recorded workshops page linked above.

Workshop Topics:

  • Brief overview of Google Colab
  • Uploading, managing, and saving data in Google Colab environment

Python & Data 1: Getting Started with Python

Workshop Topics:

  • Using Google Colab and Jupyter to work with Python
  • Python syntax, commands, functions, and packages/modules
  • Opening, viewing, and exploring data
  • Generating basic descriptive statistics from data


Python & Data 2: Manipulating & Transforming Data

Workshop Topics:

  • Selecting, sub-setting, and manipulating data
  • Transforming and generating variables
  • Handling data with missing values
  • Generating crosstabs / contingency tables

Python & Data 3: Visualizing Data & Creating Models

Workshop Topics:

  • Plotting and visualizing data using Matplotlib and Seaborn
  • Defining statistical models using both formulas and matrices
  • Fitting and inspecting statistical models (e.g. anova, linear regression)

Text Data Analysis Workshop


Text Data Analysis Workshop


  • LIVE workshops are no longer offered for this series.
  • For RECORDED workshops: Click here.

Text Data: Basics of Text Processing and Regular Expressions

The size and volume of textual data available to academic researchers is absolutely immense. Consequently, for some researchers, having the skills to process, transform, and analyze text data using computational tools is increasingly necessary for certain types of research. This workshop will introduce the fundamentals of working with and manipulating text data using scripting languages (e.g. Python, R). This includes loading, processing, and preparing text data for use with quantitative models. Although advanced natural language processing (NLP) models are not included in this workshop, some possible applications may be demonstrated if time permits. No special background knowledge or skills are required to attend. All are welcome.

Skill Requirements: Basic familiarity with Python, R, or any scripting language preferred.

Software Requirements for Hands-on Participation:

  • Participants will need a Google / Gmail account in order to access Google Colab
  • No software installation is required.

Workshop Topics:

  • Common text and string operations
  • Tokenization, transformations, and processing
  • Regular Expressions
  • N-grams and term frequencies