Aim of the Course: This
three-week course will
provide an easy
introduction to R and its
use in statistics and in
organizing data. Once
you've completed this
course you'll be able to
enter, save, retrieve,
summarize, display and
analyze data, run
simulations, construct
confidence intervals and
test hypotheses using R.
Who
Should Take This Course:
Anyone who encounters
statistics in their work
and wishes to program
their own procedures in a
convenient, widely-used,
open-source (free)
language.
Instructor:
Dr. Phillip Good, former
Calloway Professor of
Computer Science at the
University of Georgia
(Fort Valley) and graduate
of the program in
mathematical statistics at
UC Berkeley, is the author
of Introduction to
Statistics via Resampling
Methods and R (2nd ed,
Wiley, 2013), Common
Errors in Statistics (and
How to Avoid Them) (4th
edition, Wiley, 2012 with
James Hardin), Resampling
Methods (Birkhauser, 2nd
ed, 2005), Permutation,
Parametric, and Bootstrap
Tests of Hypotheses
(Springer, 3rd ed, 2004),
Manager's Guide to Design
and Conduct of Clinical
Trials (Wiley, 2nd ed.
2005), The A-Z of
Error-Free Research Using
R (CRC, 2012), and
Applying Statistics in the
Courtroom (CRC, 2001). He
has given tutorials at the
Joint Statistical Meetings
(U.S.) and Deming
Conference, lectured in
Australia, Belgium,
Bulgaria, France, Holland,
Ireland, Slovenia, and
Spain, and was twice a
traveling lecturer for the
American Statistical
Association. This is his
seventh (8th) year of
providing on-line
interactive courses.
Prerequisite:
You should have
familiarity with basic
statistical concepts. If
not, we highly recommend
our course Statistics
through Examples.
Prior use of some computer
language is helpful, but
our interactive bulletin
board plus supplementary
material guide even the
novice to successful
mastery of R.
Organization
of the Course: The
course takes place over
the Internet. 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
an alias and access to a
private bulletin board
that serves as a forum for
discussion of ideas,
problem solving, and
interaction with the
instructor. The course is
scheduled to take place
over three weeks, and
should require no more
than ten hours per week.
At the beginning of each
week, participants receive
the relevant material, in
addition to answers to
exercises from the
previous session. During
the week, participants are
expected to go over the
course materials and work
through exercises.
Discussion among
participants is
encouraged. The instructor
will provide answers and
comments.
Course
Requirements: The
optional text is Introduction
to Statistics Through
Resampling Methods and R (2nd
ed, Wiley, 2013), by Dr.
Good. The previous link
allows you to order the
text directly from Wiley.
Wiley typically offers a
15% discount to
statcourse.com customers
during checkout time.
PLEASE ORDER YOUR COPY IN
TIME FOR THE COURSE
STARTING DATE. Also, you
must have a copy of R for
the course. Click
Here to download a
free copy of R for use
during the course and
afterward.
Course
Program: The course is
structured as follows
SESSION
1: Basic Concepts
- Downloading and
Installing R
- Entering, Saving,
and Retrieving Data
- Arithmetic
Operations and Summary
Statistics
- Character Variables
and Frames
- Simple Graphics
SESSION
2: Selecting Data
Elements
- Generating
Artificial Data
- Selecting Random
Samples
- Loops and the
Bootstrap
- If ... Then
- Getting Help
SESSION
3: Testing Hypotheses
- Testing Hypotheses
- Expanding R's
capabilities
-
Downloading,
installing, and Using
R Libraries
-
Building Your Own R
Functions
