Introduction to R Programming
This course provides an easy introduction to programming in R.
Overview
This course provides an easy introduction to programming in R for those who have little or no programming experience. Topics include understanding file formats, basic R syntax, and how to use text editors to write code. You will learn to read in files, use symbols and assignments, and iterate simple loops, and the course closes with a discussion of data structures (including vectors and data frames) and subsetting.
- Introductory
- 4 Weeks
- Expert Instructor
- Tuiton-Back Guarantee
- 100% Online
- TA Support
Learning Outcomes
After taking this course you should be able to install and read data files in R. You will learn to perform various operations and apply common functions to manipulate and analyze data using basic R syntax.
- Install R and RStudio
- Write simple pseudocode and create simple flow charts
- Document your code
- Use file management and version control tools
- Perform simple arithmetic and statistical operations in R
- Read data files into R
- Create loops for iteration (e.g. for loop)
- Subset data vectors and lists
- Use apply family of functions for subsetting and basic computations
- Use simple R functions for numerical analysis
- Use simple R functions for basic graphs
- Get familiar with R Data Structures, especially vectors and data frames
- Perform data manipulation on data frames
- Perform sorting, merging of data frames
Who Should Take This Course
Those who want to start their study of programming in R, especially those with no prior programming experience.
Our Instructors
Dr. Tal Galili
Course Syllabus
Week 1
Getting Started with R
- Basic programming principles
- Flow charts
- Pseudocode
- 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
Variables, Loops and Data Structures
- Variables
- Sequences
- Simple loops (iteration)
- Data structures
- Exploring data
- Subsetting data
Week 3
apply and other Functions
- apply function
- Special values
- Packages
- Useful functions
Week 4
Multidimensional Data
- Overview of vectors, vector manipulation
- Factors
- Attributes
- Lists, matrices, and arrays
- Data Frames
Class Dates
2025
Instructors: Dr. Tal Galili
Instructors: Dr. Tal Galili
Instructors: Dr. Tal Galili
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Additional Information
Time Requirements
This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.
Homework
The homework in this course consists of short answer questions to test concepts, guided exercises in writing code, and guided data analysis problems using software.
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.
Software
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.
Course Fee & Information
Enrollment
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.
Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.
Group Rates
Contact us to get information on group rates.
Discounts
Academic affiliation? In most courses you are eligible for a discount at checkout.
New to Statistics.com? Click here for a special introductory discount code.
Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.
Options for Credit and Recognition
This course is eligible for the following credit and recognition options:
No Credit
You may take this course without pursuing credit or a record of completion.
Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.
CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.
ACE CREDIT | College Credit
This course has been evaluated by the American Council on Education (ACE) and is recommended for college credit. For recommendation details (level, and number of credits), please see this page. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.
ACE Digital Badge
Courses evaluated by the American Council on Education (ACE) have a digital badge available for successful completion of the course.
INFORMS-CAP
This course is 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.
Supplemental Information
There is no supplemental content for this course.