Most statistical software has a graphical interface
available. Why learn programming? Hadley Wickham, a leading member of the
R development community, lists the advantages: "reproducibility,
automation and communication" (From an interview in "Decision Stats").
Dr. Wickham will offer his online course, "Programming in R". For more details please visit at http://www.statistics.com/Rprogramming.
In "Programming in R", you will hone your skills to work with a variety of data types and data sources in R. You'll also learn some techniques for programming "in-the-large", when you are trying to provide a suite of functions to flexibly solve a large class of problems. In particular, you'll learn more about functions, environments and closures, and the basics of object oriented programming with S3.
Dr. Hadley Wickham is the author of "ggplot2: Elegant Graphics for Data Analysis (Use R)" and a contributor to Cook & Swayne's "Interactive and Dynamic Graphics for Data Analysis: Using R and GGobi" (2007). His research interests include interactive and dynamic graphics, developing practical tools for data analysis, and in gaining better understanding of complex statistical models through visualization. An Assistant Professor at Rice University, Dr. Wickham has developed 15 R projects, and written numerous articles, chapters, and other papers and in 2006 he won the John Chambers Award for Statistical Computing for his work on the ggplot and reshape R packages. Participants can ask questions and exchange comments with Dr. Wickham via a private discussion board throughout the period.
Who Should Take This
Course?
Statistical analysts who want to use R as a serious
statistical computing tool.
Course Program:
Course outline: The course is structured as
follows
SESSION 1: Functions and Controlling Evaluation
In this session you'll learn how to go beyond the
basics to make closures, functions that are written by other functions. To
understand how closures work, we'll go over R's scoping rules and discuss how
environments and frames work. To show why closures are worth learning about,
we'll give some examples using them for maximum likelihood estimation, and for
creating functions that remember what happened last time they were called.
SESSION 2: Strings and Dates
Learn the basics of string manipulation (with regular
expressions) and working with dates. Base R provides some functions to deal
with these common data types, but they're not very friendly. We'll briefly
cover base R functions, then move on to two new packages, stringr and
lubridate, that have been designed from the ground up to be consistent and easy
to use.
SESSION 3: XML and HTML
For xml, you'll learn the basics of xpath expressions,
which make it easy to pull out the pieces that you're interseted in, and how to
avoid some of the pitfalls of the xml package.
SESSION 4: Working with Databases
In this session you will learn the basics of working
with external databases and xml files. We'll cover some of the range of options
for accessing external databases, and some convenient tools for converting
large local datasets into databases to make it faster to retrieve subsets of
interest.
You will be able to ask questions and exchange comments with the instructors via a private discussion board throughout the course. The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week. Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.
For Indian participants statistics.com accepts
registration for its courses at special prices in
Indian Rupees through its partner, the Center for eLearning and Training
(C-eLT), Pune (www.c-elt.com).
Call: 020 66009116
Websites:
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