Short courses
will be offered
Wednesday, October 7 &
Saturday, October 10
8:30 a.m. to 5:30 p.m.
(The fee for each course includes coffee breaks and lunch. Registration is limited.)
A Corporate Perspective: Financial Savvy for Statisticians
by Frederick W. Faltin and Donna M. Faltin
Sponsored by ASA-Q&P
Wednesday, October 7, 2009
$280 ($250 + $30 for Materials)
All of a company’s activities impact the financial well-being of its owners/shareholders and employees in one way or another. So finance, broadly defined, is an all-pervasive element of the corporate environment. This course will discuss the role of corporate finance, the financial issues that drive decision making and market perceptions, and key topics needed for an understanding of corporate financial management. Along the way, we’ll acquaint attendees with the language of financial management, with the broader aim of helping them to better integrate into the corporate mainstream and to enhance their ability to contribute to, and prosper within, their respective organizations.
Conceptual foundations will include: risk & return; principles of borrowing/lending, including hedging & leasing; portfolio theory; insurance (buying, selling, and pricing risk); Present Value; and international finance. Illustrations will include examples taken from recent headlines on subprime lending, bank failures, etc.
Specifics of corporate finance will include: financial performance metrics; Income Statements and Balance Sheets; financial planning; accounting practices; capital budgeting; dividend policy; and capital structure. Applications to recent events will include examples of corporate fraud and the tenets of Sarbanes-Oxley.
Attendees will receive course notebooks with presentation contents; no
specific software is required, and laptops are optional.
A Short Course on Industrial Split Plot Experiments
by Geoff Vining
Sponsored by ASQ-STAT
Wednesday, October 7, 2009
$250
Spilt-plot experiments involve two sets of factors. One set consists of factors that are hard and/or expensive to change. The other set consists of factors that are much easier and/or less expensive to change. Most industrial processes involve both types of factors.
The standard designs and analyses taught in most Six-Sigma Black Belt courses are not appropriate for such experimental situations. This course illustrates the proper experimental protocol and analysis.
Topics covered in this course include a historical background, hard-to-change vs. easy-to-change factors, complete sub-plot experiments within each whole-plot, fractional factorials within each whole-plot, proper residual analysis, lack of fit and second-order split-plot experiments. The course will use Minitab, JMP, and R for the analyses.
Expanding Your Factorial Two-Level Experimentation Toolset
by Robert Mee
Sponsored by ASA-SPES
Saturday, October 10, 2009
$320 ($250 + $70 for textbook)
This workshop is intended to equip practitioners to select and analyze fractional factorial designs more knowledgeably.
The workshop will provide an introduction to the new book “A Comprehensive Guide to Factorial Two-Level Experimentation.” Each student will receive a copy of this textbook. The book contains 50 published experiments, many of which will be utilized to illustrate the choice of design and proper data analysis.
Orthogonal array designs that are not regular fractional factorials will receive particular emphasis. The importance of run order restrictions will be explained, including blocking, split-unit, and trend-free designs.
Introduction to Regression Modeling
by Bob Brill
Sponsored by ASQ-CPID
Saturday, October 10, 2009
$250
This course is designed for those who are interested in using and/or creating regression models but have not had any formal training on these methods. (It is assumed that the student has had an introductory course on statistics or equivalent.)
After a brief review of some of the relevant intro to statistics topics the student will learn how linear least squares regression curves are fit to data, how to interpret all the output from a typical software package (Minitab will be used in this course), how to assess how good the model is and how to intelligently use it.
Some of the topics covered will be the sum of squares and degrees of freedom decomposition, corresponding F-tests, goodness of fit, lack of fit, model R2, adjusted R2, analysis of residuals, tests of significance for the model coefficients, prediction and confidence intervals, the use of dummy variables and much more.
This is not a math course, we let the software worry about doing that right. The emphasis will be on learning the concepts by working with real world examples. If time permits some exploratory and nonlinear regression methods will be presented.
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Pdf of Short Courses |