To support the campus's NIH All of Us access and research, the AOK Library will be hosting a free 5-series workshop on R. R is a free programming language for statistical and computing data visualization.
Basics of R: Downloading & installing R and R Studio,
Google Colab, and loading datasets
Please watch this video before attending the March 5th session on data wrangling.
[This is an asynchronous video. All other sessions are online with instructor.]
March 5 | 11 am - 12:30 pm | Webex
Click here to join.
Data Wrangling (Management) Techniques
In this session, learn the basics for inspecting and manipulating datasets, creating subsets of data, creating and renaming variables, handling missing data, using conditional logic, and generating random samples.
March 8 | 11 am - 12:30 pm | Webex
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Summarizing and Visualizing Your Data
In this session, learn how to simply generate summary statistics for raw data and by group. Attendees will do this for both continuous and categorical variables. Participants will learn how to use GGPLOT2 and extended packages to visualize their data using a series of different types of data visuals (histograms, line charts, bar charts, violin plots, etc.).
March 12 | 11 am- 12:30 pm | Webex
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Merging, Appending, and Reshaping Your Data
In this session, participants will learn how to merge distinct datasets. This may be useful if you want to append All of Us data with your own customized dataset that you upload. We will learn how to bind, append, join/merge data. We will also learn how to reshape/reorient/pivot data from wide to long and back.
March 15 | 11 am- 12:30 pm | Webex
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Data Analyses
In this session, attendees will explore how to easily analyze their data. Dr. Eric Stokan will cover such analytic techniques as hypothesis testing using t-tests, correlations, and ANOVA. He will also discuss linear, logistic, fixed effects, and difference-in-differences regression or other techniques of interest for the group as identified in session 1. Attendees will learn how to use diagnostic and assumption checks in R, and produce visuals based on their data analyses. Dr. Stokan will also provide resources for engaging in machine learning practices.