R Programming – Introduction Part 2

R Programming – Introduction Part 2

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

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

$549 | Enroll Now
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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.

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.

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.

See Instructor Bio

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

2021

Mar 12, 2021 to Apr 9, 2021

2022

No classes scheduled at this time.

2023

No classes scheduled at this time.

Send me reminder for next class

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.

Introductory Statistics

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.

Recommended

We recommended, but do not require as eligibility to enroll in this course, an understanding of the material covered in these following courses.

R Programming – Introduction Part 1

This course provides an easy introduction to programming in R.
Topic: Data Science, Using R | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: Jan 15, 2021, May 14, 2021, Sep 10, 2021

What Our Students Say​

The instructor Joris Mays was very effective, especially in the discussion board where his feedback was timely, clear and very thorough.

Peter Varisco
Corporate Vice President - Advanced Analytics at New York Life Insurance Company

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.

Margaret Palmisano

Frequently Asked Questions

Can I transfer or withdraw from a course?

We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.

  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.

Please see this page for more information.

Who are the instructors at the Institute?

The Institute has more than 60 instructors who are recruited based on their expertise in various areas in statistics. Our faculty members are:

  • Authors of well-regarded texts in their area;
  • Advisory board members;
  • Senior faculty; and
  • Educators who have made important contributions to the field of statistics or online education in statistics.

The majority of our instructors have more than five years of teaching experience online at the Institute.

Please visit our faculty page for more information on each instructor at The Institute for Statistics Education.

Please see our knowledge center for more information.

What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

Please see our course search or knowledge center for more information.

Do your courses have for-credit options?

Our courses have several for-credit options:

  • Continuing education units (CEU)
  • College credit through The American Council on Education (ACE CREDIT)
  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)

Please see our knowledge center for more information.

Is the Institute for Statistics Education certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: http://www.schev.edu

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

Related Courses

Course Icon

R for Statistical Analysis

This course will teach you how to use R for basic statistical procedures.
Topic: Data Science, Using R | Skill: Intermediate | Credit Options: CAP, CEU

R Programming – Intermediate

This course will teach experienced data analysts a systematic overview of R as a programming language, emphasizing good programming practices and the development of clear, concise code. After completing the course, students should be able to manipulate data programmatically using R functions of their own design.
Topic: Data Science, Using R | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Mar 12, 2021, Sep 17, 2021

R Programming – Introduction Part 1

This course provides an easy introduction to programming in R.
Topic: Data Science, Using R | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: Jan 15, 2021, May 14, 2021, Sep 10, 2021

Additional Course 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.

Please order a copy of your course textbook prior to course start date.

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.

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?” 

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.

Miscellaneous

There is no additional information for this course.

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R Programming – Introduction Part 2
$549 | Enroll Now
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