R Programming - Introduction 1
Taught by Dr. Tal Galili

R Programming - Introduction 1

taught by Tal Galili


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Aim of Course:

In this online course, “R Programming Intro 1,” you will be introduced to basic concepts in computer programming via R - it is for those who have had little or no experience in programming.  You will learn how to get going in R from the beginning, understand file formats and basic R syntax, and learn about using text editors to write code.  You will learn how to read in files, use symbols and assignments, and iterate simple loops.  The course closes with discussion of data structures and subsetting.  Note:  Those with some familiarity with programming should probably start with R Programming Introduction 2.  After taking this course you should be able to

  • Install R
  • Read data files into R
  • Understand assignment operations
  • Create loops for iteration
  • Subset data
  • Apply functions 
Course Program:

WEEK 1: Getting Started with R

  • Installing, starting and stopping R
  • file operations and file formats
  • writing code and text editors
  • basic R syntax
  • reading files
  • symbols and assignment

WEEK 2: Loops

  • sequences
  • simple loops (iteration)

WEEK 3: Data Structures

  • data structures
  • subsetting
  • assigning to subsets

WEEK 4: Data Manipulation

  • apply Functions

R Programming - Introduction 1

Who Should Take This Course:
Those who want to start their study of programming in R, especially those with no prior programming experience.  If you do have some programming experience and want to learn R, you could consider starting directly with R Programming Intro 2.
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 1 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 course text is Introduction to Data Technologies by Paul Murrell. It may be purchased from the publisher Chapman and Hall/CRC Press. The text is also available online here in both PDF and HTML formats.

You must have a copy of R for the course. Click Here for information on obtaining a free copy, including installation instructions.  Installation will be covered in the first week of the course, but you should try installing R before the course starts, so that any issues you encounter can be addressed early.



January 17, 2020 to February 14, 2020 May 29, 2020 to June 26, 2020 September 25, 2020 to October 23, 2020

R Programming - Introduction 1


January 17, 2020 to February 14, 2020 May 29, 2020 to June 26, 2020 September 25, 2020 to October 23, 2020

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.

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