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Programming R for Analytics

94-842

Units: 6

Description

An introduction to R, a widely used statistical programming language. Students will learn to import, export and manipulate different data types, analyze datasets using common statistical methods, design, construct and interpret statistical models, produce a variety of different customized graphical outputs, create scripts and generate reproducible reports. There will be a focus on using this experience to apply these skills in public policy areas.

Prerequisites: 91-801 Statistical Methods for Managers, or 95-796 Statistics for IT Managers

A good knowledge of statistics is preferred, but this course is focused on anyone wanting to learn the basics of the R language and how to use the tools R offers to be able to do basic data analysis, statistical calculations, create graphical output and generate reproduceable reports using R Markdown.

Learning Outcomes

  • Import, export and manipulate various types of stored data and datasets.
  • Produce statistical summaries of continuous and categorical data.
  • Produce basic graphics using standard functions.
  • Create more advanced graphics using ggplot2 and plot.ly packages.
  • Perform basic statistical and hypothesis tests.
  • Develop classification and regression models and generate common performance metrics.
  • Create reproducible reports with R Markdown.

Prerequisites Description

91-801 Statistical Methods for Managers, or 95-796 Statistics for IT Managers

Syllabus