Carl H. Lindner College of BusinessCarl H. Lindner College of BusinessUniversity of Cincinnati

Carl H. Lindner College of Business

Introduction to "R"

OCT 5 & 6, 2017

Course Description: R is one of the fastest growing programimng languages and tool of choice for analysts and data scientists.  In part, R owes its popularity to its open source distribution and massive user community.  In this course, we will help both new and existing R users master the basics of R.   There will be an emphasis on using hands on exercises and real world datasets.

Upon successfully completing this course, students will:

  • Be up and running with R
  • Understand the different types of data R can work with
  • Understand the different structures in which R holds data
  • Be able Import data into R
  • Perform basic data wrangling activities with R
  • Compute basic descriptive statistics with R
  • Visualize their data with base R and ggplot graphics

Course Outline

Day One


  • Downloading R & RStudio
  • The R environment
  • Getting help
  • Managing your directory
  • R as a Calculator
  • Simple objects & assignment
  • Vectors
  • Working with packages

 Importing/Exporting Data

  • Built-in data
  • Text files
  • Excel files
  • Scraping online tabular files

 Data Structures

  • Vectors
  • Matrices
  • Lists
  • Data frames

 Data Types

  • Numbers
  • Character strings
  • Factors
  • Dates
  • Logical

 Tidy Data

  • Managing wide & long data
  • Splitting & uniting variables

Day Two

Transforming & Manipulating Data

  • Selecting variables
  • Filtering variables
  • Summarizing
  • Ordering
  • Creating new variables
  • Merging data sets

 Base R Plotting

  • Strip charts
  • Histograms
  • Density plots
  • Box plots
  • Bar charts
  • Dot plots
  • Scatter plot
  • Line charts

 Advanced Plotting with ggplot

  • geoms
  • Overfitting
  • Color, size & shape aesthetics
  • Small multiples (faceting)
  • Scales, axes & legends
  • Themes

 Putting it all together

  • Case study 1
  • Case study 2



Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Course Location:
U-Square. Room 352
225 Calhoun Street
Cincinnati. OH 45219   (google map link)

Course Instructor:

Brad Boehmke

Hello! I’m Brad Boehmke, a computational economist focused on applying advanced evidence-based analytics to provide decision makers robust understanding of economic behavior, performance, and potential policy impacts across an organization.

I work on empirical econometric research, write data analysis softwareteach people about business analytics and R programming, write books, and create digital projects.

I do my work as an Assistant Professor of Logistics and Supply Chain Management at the Air Force Institute of Technology Department of Operational Sciences and as an Adjunct Assistant Professor of Business Analytics at the University of Cincinnati Lindner College of Business. Previously, I was a Senior Operations Research Analyst with the Air Force and spent many years developing life cycle forecasting, risk and decision analysis models.