COURSE DESCRIPTION

This course introduces essential concepts and techniques of programming in the R computer programming language. It covers R variables, data types, arithmetic and logical operations, environments, functions, flow control and loops. The course also discusses using R to get, clean, and transform data, which is a critical step in any data analysis project. Upon completion of this course, students should be able to set up an R programming environment and perform common R programming tasks.

COURSE TOPICS

R programming environment setup and operation
Common arithmetic and logical operations in R
Major variable classes in R
Major data structures in R
Environments and functions
Flow control and loops
Getting, cleaning, and transforming data

COURSE OBJECTIVES

After completing this course, you should be able to:

CO1 setup and use an R programming environment;

CO2 perform common arithmetic and logical operations in R;

CO3 create major data structures with different variable classes in R;

CO4 use major data structures with different variable classes in R;

CO5 perform common operations on R environments;

CO6 write functions, flow control statements, and loops in R; and

CO7 read, clean, and transform data in R.

COURSE MATERIALS

You will need the following materials to complete your coursework. Some course materials may be free, open source, or available from other providers. You can access free or open-source materials by clicking the links provided below or in the module details documents. To purchase course materials, please visit the University's textbook supplier.

Required Textbooks

Cotton, R. (2013). Learning R. Sebastopol, CA: O'Reilly Media.
ISBN-13: 978-1449357108

COURSE STRUCTURE

R Programming (COS-206) is a three-credit online course, consisting of six (6) modules and a Final Project. Modules include an overview, topics, learning objectives, study materials, and activities. Module titles are listed below.

Module 1—R Development Environment and Using R as a Calculator
Course objectives covered in this module: CO1 and CO2
Module 2—R Variables, Vectors, Matrices, and Arrays
Course objectives covered in this module: CO3
Module 3—Lists, Data Frames, R Environments, and Functions
Course objectives covered in this module: CO3, CO4, and CO5
Module 4—Strings, Factors, Flow Control Statements, and Loops
Course objectives covered in this module: CO3, CO4, and CO6
Module 5—Advanced Looping and Getting Data
Course objectives covered in this module: CO6 and CO7
Module 6—Cleaning and Transforming Data
Course objectives covered in this module: CO7

ASSESSMENT METHODS

For your formal work in the course, you are required to participate in online discussion forums, complete programming assignments, and complete a Final Project. See below for details.

Consult the Course Calendar for due dates.

Promoting Originality

One or more of your course activities may utilize a tool designed to promote original work and evaluate your submissions for plagiarism. More information about this tool is available in this document.

Discussion Forums

You are required to participate in six (6) graded discussion forums. Discussion forums are on a variety of topics associated with the course modules. There is also an ungraded but required Introductions Forum in Module 1.

Programming Assignments

You are required to complete six programming assignments.

Final Project

The Final Project, which you will complete in Week 12, consists of the development of a series of R Programming Scripts.

GRADING AND EVALUATION

Your grade in the course will be determined as follows:

Discussion Forums (6)—15%
Programming Assignments (6)—60%
Final Project—25%

All activities will receive a numerical grade of 0–100. You will receive a score of 0 for any work not submitted. Your final grade in the course will be a letter grade. Letter grade equivalents for numerical grades are as follows:

A	=	93–100	C+	=	78–79
A–	=	90–92	C	=	73–77
B+	=	88–89	C–	=	70–72
B	=	83–87	D	=	60–69
B–	=	80–82	F	=	Below 60

To receive credit for the course, you must earn a letter grade of C or better (for an area of study course) or D or better (for a course not in your area of study), based on the weighted average of all assigned course work (e.g., exams, assignments, discussion postings, etc.).

STRATEGIES FOR SUCCESS

First Steps to Success

To succeed in this course, take the following first steps:

Read carefully the entire Syllabus, making sure that all aspects of the course are clear to you and that you have all the materials required for the course.
Take time to read the entire Online Student Handbook. The Handbook answers many questions about how to proceed through the course and how to get the most from your educational experience at Thomas Edison State University.
Familiarize yourself with the learning management systems environment—how to navigate it and what the various course areas contain. If you know what to expect as you navigate the course, you can better pace yourself and complete the work on time.
If you are not familiar with Web-based learning be sure to review the processes for posting responses online and submitting assignments before class begins.

Study Tips

Consider the following study tips for success:

To stay on track throughout the course, begin each week by consulting the Course Calendar. The Calendar provides an overview of the course and indicates due dates for submitting assignments, posting discussions, and scheduling and taking examinations.
Check Announcements regularly for new course information.

ACADEMIC POLICIES

To ensure success in all your academic endeavors and coursework at Thomas Edison State University, familiarize yourself with all administrative and academic policies including those related to academic integrity, course late submissions, course extensions, and grading policies.

For more, see: