This course is a continuation of the introduction to R programming.
This course is a continuation of the introduction to R programming.
In this course you will continue your introduction to R programming. You will learn how R works with numeric vectors, 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. Some prior programming experience and some familiarity with an installed R system is required.
After completing this course you should be able to create and work with numeric vectors and summaries, and deal with special values. You will learn to work with text, matrices, data frames, lists and date expressions.
Take this course if you want to continue your R programming education.
Vectors
Text
Data frames
Dates
Jul 12, 2019 to Aug 9, 2019
Nov 15, 2019 to Dec 13, 2019
Mar 13, 2020 to Apr 10, 2020
Jul 17, 2020 to Aug 14, 2020
Nov 13, 2020 to Dec 11, 2020
Mar 12, 2021 to Apr 9, 2021
R Programming 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.
We assume you are versed in statistics or have the equivalent understanding of topics covered in our Statistics 1 and Statistics 2 courses. but do not require them as eligibility to enroll in this course. Please review the course description for each of our introductory statistics courses, estimate which best matches your level of understanding of the material covered in these courses, then take the short assessment test for that course. If you can not answer more than half of the questions correctly, we suggest you take our Statistics 1 and Statistics 2 courses prior to taking this course.
We recommended, but do not require as eligibility to enroll in this course, an understanding of the material covered in these following courses.
The course, Introduction to R Programming Part Two, taught by Joris Meys was EXCELLENT! All of the course materials were extremely helpful in allowing me not only to understand the details of R programming but also to gain a solid perspective on the fundamentals of R coding. The feedback on the assignments was very detailed and the explanations included why certain approaches of coding were preferable to others. I really enjoyed this course and I learned a great deal.
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.
This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.
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.
The required text for this course is R For Dummies, by de Vries and Meys, second edition.
Please order a copy of your course textbook prior to course start date.
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.
Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?”
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.
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 the the upper division baccalaureate degree, 3 semester hours in data mining, statistics, or computer science. 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.
There is no supplemental content for this course.
There is no additional information for this course.
