R Trainings in LinkedIn Learning

“R Essential Training: Wrangling and Visualization” and “R Essential Training Part 2: Modeling Data” have all the commands that a beginner needs to know to continue by his or her own. These trainings provide clear-to-understand content and exercise files for practice.

To login into LinkedIn Learning, click on the LinkedIn Learning tab above for individual courses or follow the LinkedIn Learning Path to advance your knowledge of RTools.

After watching these trainings, users will have a very good understanding about how R and R Studio work, and you will be able to:

  • Import data from several sources
  • Explore variables: frequencies, descriptive, correlations, and contingency tables
  • Create visualizations for one or more variables and for categorical and scale variables
  • Wrangle data and recode different types of variables
  • Make inference about the mean and the proportion for one or more variables
  • Carry out ANOVA, correlation, linear regression, multiple linear regression, and contingency tables.
  • If you are familiar with multivariate statistical analyses and machine learning, you could watch cluster analysis, principal component analysis, decision trees, and random forest analysis.

After completing these trainings, you can further your learning by watching other videos that fit your needs. Below are five LinkedIn trainings that we recommend:

  • Data wrangling in R 2017 (4h 12 min)
  • Cleaning Bad Data in R (1h 54 min)
  • Data visualization in R with ggplot2 (2h 27 min)
  • Healthcare Analytics: Regression in R (4h 2 min)
  • 11 Useful Tips for Regression Analysis (55 min)

All commands taught by these seven trainings can be run in the most current versions of R (4.1.1) and R Studio (1.4.1717). The only exception is geospatial visualization in “Data Visualization in R with ggplot2” because it requires the installation of the package “Rtools”, which is not available in R v.4.1.1. In addition, the user will not be able to work with the cases studies.

You are ready to go. Once you complete each training, you will receive a certificate of completion.

R Programming Training Offered by UFIT

If you are interested in R programming specifically designed for basic statistical analyses at the graduate level, we offer the online and self-paced training “R Programming Training: An Introduction for Data Analysis and Graphics.” Click here for registration.

Time Commitment

R Essential Training: Wrangling and Visualization = 4 h 18 min

R Essential Training Part 2: Modeling Data = 3 h 59 min

 

Who's it for?

Faculty, Student, Staff, TA / Grad Asst

Format

Online: self-paced

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