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Begins
7th June 2013
Aim
of the Course:
This 3-week course will
introduce you to the
resampling methods--the
bootstrap, CART, and the
permutation test and then
show you how to apply them
in your work with
practical examples from
the medical device and
pharmaceutical industries
including how to obtain
estimates of required
sample size from empirical
distributions and the
analysis of contingency
tables and cross-over
designs.
Who
Should Take This Course: Anyone who wants to make more effective use of statistics in
their work in the
pharmaceutical and medical
device industries.
An
existing undergraduate
background in estimation
and testing hypotheses is
essential.
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
U.C. Berkeley, is the
author of Practitioner's
Guide to Resampling
Methods, (CRC, 2011), A-Z
of Error-Free Research (CRC,
2012), Manager's Guide
to Design and Conduct of
Clinical Trials
(Wiley, 2nd ed
2006), Resampling
Methods (Birkhauser,
3rd ed, 2005), Introduction
to Statistics via
Resampling Methods and
Excel (Wiley, 2005), Common
Errors in Statistics (and
How to Avoid Them)
(Wiley, 4th ed 2012) with
James Hardin), Permutation,
Parametric, and Bootstrap
Tests of Hypotheses
(Springer, 3rd ed, 2004),
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 a traveling
lecturer for the American
Statistical Association.
This is his sixth (6th)
year of providing on-line
interactive courses.
Prerequisite:
You should have
familiarity with basic
statistical concepts.
If not, we highly
recommend Introduction
to Statistics via
Resampling Methods and R
(2nd ed, Wiley, 2013). Prior
use of R, S-Plus or Stata
is helpful.
Regretfully, few of these
routines are available in
SAS.
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 about 10
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
Resampling Methods (Birkhauser,
3rd ed, 2005) by Dr. Good. The previous link allows you to order the
text directly from
Birkhauser. Birkhauser
typically offers a 15%
discount to statcourse.com
customers during checkout
time. If you'd prefer an
electronic textbook, you
may download the
hyper-linked Practitioner's
Guide. PLEASE
ORDER YOUR COPY IN TIME
FOR THE COURSE STARTING
DATE. During the course,
we will download from
cytel.com and make use of
a trial copy of StatXact
for analyzing contingency
tables.
Course
Program:
The course is structured
as follows
SESSION
1:
The Bootstrap
SESSION
2: Permutation
Tests
-
Practical
Applications
-
Comparing
Means
-
Multivariate
Data
-
Behrens-Fisher
Problem
-
Comparing
Variances
SESSION
3: Applying
the Concepts
Cost:
The full cost of this
three-week interactive
on-line course is only
$229. Early-bird discount.
Students, faculty and
research workers at
academic institutions are
eligible for a further
discount. Just send an
email from your academic
email account to courses@statcourse.com
to receive a discount
coupon worth $35 toward
the cost of the course.
Immediately
after your payment is
credited, you will receive
an email giving you a
password, sign up
instructions, and the web
address (URL) of the
course material. Note that
you will not be able to
access this address until
the start date of the
course. |
