Introduction to R - Data Handling
Dr. Paul MurrellAim of Course:
This course will provide a basic introduction to R, and its use in organizing and exploring data. The emphasis is on understanding and working with fundamental R data structures and we will introduce some basic R programming techniques. Once you've completed this course you'll be able to enter, save, retrieve, manipulate, and summarize data using R; you will also have the proper foundation to build your programming skills in R and take advantage of the full power of R.Please see also our course Introduction to R-Statistical Analysis, which is suitable for those needing to get up to speed very quickly in certain standard statistical analysis routines, without a systematic introduction to programming.
Who Should Take This Course:
Anyone who wants to wants to learn the fundamentals of data handling and programming in R.Course Program:
The course is structured as follows- The R command line
- Function calls, symbols, and assignment
- Packages
- Getting help on R
- Data Types and data structures
- Subsetting data
- Type coercion
- Text files, XML, Spreadsheets, and binary files
- Large data sets
- Tabulating and aggregating
- Merging, Splitting and Reshaping
- Text Processing
- Data Formatting
The Instructor:
Dr. Paul Murrell is Senior Lecturer in the Department of Statistics at the University of Auckland, New Zealand. Dr. Murrell has been a member of the core development team for R since 1999, with a focus on the graphics system in R. He is the past Chair of the Section for Statistical Graphics of the American Statistical Association. He has recently served as Editor-in-Chief of R News, the newsletter of the R project, and is an Associate Editor for Computational Statistics and The Journal of Statistical Software.Organization of the Course:
The course takes place over the internet, at statistics.com. 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. The course is scheduled to take place over 4 weeks, and typically requires 15 hours per week. 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 and work through exercises. Discussion among participants is encouraged. The instructor will provide answers and comments.Certificates and Grades:
You may be interested only in learning the material presented, and not be concerned with grades or certificates. Or you may be enrolled in a statistics.com Program in Advanced Statistical Studies that requires demonstration of proficiency in the subject, in which case your work will be assessed for purposes of issuing a grade. Or you may require only a "Certificate of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's). As you begin the class, you will be asked to specify your category.Credit:
This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a certificate will be issued by statistics.com, upon request.Dates:
Mar. 5 - Apr. 2, 2010Sep. 17 - Oct. 15, 2010
Click here to be notified of future course offerings.
Participants gain access to the online materials on the first day of the course, and typically spend about 15 hours per week (at their convenience). You retain full access to course materials, including discussion board, for two weeks after the course closing date.
Level:
introductory/intermediatePrerequisite:
There is no statistical requirement. Having written computer code before would be helpful, but this is not assumed.Course Text:
The course text is Introduction to Data Technologies by Paul Murrell. It that may be purchased from Chapman Hall. It 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.Registration:
Register Online - $469Register Online (academic) - $369 (you must be affiliated with a college, university or high school)
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. Please use this printed registration form, for these and other special orders.
Consider registering for this course together with two other R courses as part of our special 3 course package registration for tuition savings.
Note: 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.
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