R Programming - Introduction 2
Taught by Mr. Joris Meys

R Programming - Introduction 2

taught by Joris Meys


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Aim of Course:

In this online course, “R Programming Intro 2,” you will continue your introduction to R programming. You will learn how R works with numeric vectors and special values, and how to deal with special values.  You will start working with R to handle text data, and learn about regular expressions, dates, classes and generic functions, as well as matrices, data frames and lists.  After completing this course you should be able to

  • Create and work with numeric vectors and summaries
  • Deal with special values
  • Work with regular expressions in text
  • Process text with search, replace, split and paste operations
  • Work with matrices, data frames and lists
  • Process date expressions so they can be used in analysis


Course Program:

WEEK 1: Vectors

  • numeric vectors
  • special values
  • numeric summaries

WEEK 2: Text

  • text processing
  • regular expressions
  • search, replace, split, paste

WEEK 3: Data Frames

  • matrices and data frames and lists
  • data processing

WEEK 4:  Dates

  • dates
  • classes and generic functions


Homework in this course consists of guided exercises in writing code.

In addition to assigned readings, this course also has practice exercises, supplemental readings available online, and a supplemental archive of prior course discussions.

R Programming - Introduction 2

Who Should Take This Course:

Take this course if you want to continue your R programming education.

R Programming - Introduction 1 or some prior programming experience and some familiarity with an installed R system.  Statistics is not a requirement, but familiarity with some basic statistical notation will help (e.g. the means, deviations and summations involved in calculating standard deviation).
Organization of the Course:

This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Options for Credit and Recognition:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
  1. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. Certificate - You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. CEUs and/or proof of completion - You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course,  CEU's and a record of course completion will be issued by The Institute, upon request.
  4. Digital Badge - Courses evaluated by the American Council on Education have a digital badge available for successful completion of the course.  
  5. Other options - Statistics.com Specializations, INFORMS CAP recognition, and academic (college) credit are available for some Statistics.com courses

Specializations are an easy way for you to demonstrate mastery of a specific skill in statistics and analytics. This course is part of the R Programming Specialization which covers the basics of R Programming all the way to advanced techniques.

College credit:
R Programming - Introduction 2 has been evaluated by the American Council on Education (ACE) and is recommended for the lower-division baccalaureate/ associate degree category, 3 semester hours in computer science, information systems, or statistics. Note: The decision to accept specific credit recommendations is up to each institution. More info here.

This course is also recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam, and can help CAP® analysts accrue Professional Development Units to maintain their certification .
Course Text:

The required text for this course is R For Dummies, by de Vries and Meys, second edition.



You will need both R (download here) and RStudio (download here).  RStudio is an editing and development environment that is especially designed as a place to write R code.  Both programs are free.



November 15, 2019 to December 13, 2019 March 13, 2020 to April 10, 2020 July 17, 2020 to August 14, 2020 November 13, 2020 to December 11, 2020 March 12, 2021 to April 09, 2021

R Programming - Introduction 2


November 15, 2019 to December 13, 2019 March 13, 2020 to April 10, 2020 July 17, 2020 to August 14, 2020 November 13, 2020 to December 11, 2020 March 12, 2021 to April 09, 2021

Course Fee: $549

Do you meet course prerequisites? What about book & software? (Click here to learn more)

We have flexible policies to transfer to another course, or withdraw if necessary (modest fee applies)

Group rates: Email jdobbins "at" statistics.com to get information on group rates. 

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.

The Institute for Statistics Education is certified to operate by the State Council of Higher Education in Virginia (SCHEV).

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