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R Programming – Introduction Part 2

R Programming – Introduction Part 2

This course is a continuation of the introduction to R programming.

Overview

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.

  • Introductory, Intermediate
  • 4 Weeks
  • Expert Instructor
  • Tuiton-Back Guarantee
  • 100% Online
  • TA Support

Learning Outcomes

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.

  • 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

Who Should Take This Course

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

Our Instructors

Mr. Joris Meys

Mr. Joris Meys

Joris Meys is a statistical consultant in the Biostatistics Department at the University of Ghent.  He is the co-author (with Andrie de Vries) of R for Dummies (Wiley, 2012).  Joris is an accomplished R programmer, and produces R packages both for specific research projects and, via R-Forge, R packages for more general application.  His statistical expertise is in the areas of ecotoxicology, analysis of environmental data, clinical researchand meta analysis.

Course Syllabus

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

Class Dates

2023

11/10/2023 to 12/08/2023
Instructors: Mr. Joris Meys

2024

03/08/2024 to 04/05/2024
Instructors: Mr. Joris Meys
07/12/2024 to 08/09/2024
Instructors: Mr. Joris Meys
11/08/2024 to 12/06/2024
Instructors: Mr. Joris Meys

2025

03/14/2025 to 04/11/2025
Instructors: Mr. Joris Meys
07/11/2025 to 08/08/2025
Instructors: Mr. Joris Meys
11/14/2025 to 12/12/2025
Instructors: Mr. Joris Meys

Prerequisites

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.

Introduction to R Programming

This course provides an easy introduction to programming in R.
  • Skill: Introductory, Intermediate
  • Credit Options: ACE, CAP, CEU
Karolis Urbonas
Susan Kamp
Stephen McAllister
Amir Aminimanizani
Elena Rose
Leonardo Nagata
Richard Jackson

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R Programming – Introduction Part 2

Additional Information

Organization of 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 Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

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.

Course Text

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

Software

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.

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

Literacy, Accessibility, and Dyslexia

At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:

 

Chrome

 

Firefox

 

Safari

  • Navidys (for colorblindness, dyslexia, and reading difficulties)
  • HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)

Miscellaneous

There is no additional information for this course.

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R Programming – Introduction Part 2