Project outline
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Proposal due to 1st of June, 2015, 9:00 a.m. via e-mail
Business description due to 5th of June, 2015, 9:00 a.m. via e-mail
market strategies due to 11th of June, 2015, 9:00 a.m. via e-mail
competitive analysis due
ST305 / ST410
Designed Experiments
Lecture 23: Optimal Design
- an informal approach
Example: Optimum allocation
A completely randomised design is to be used in an
experiment to compare three treatments. The three pairwise
contrasts are all of great inter
DESIGNED EXPERIMENTS 2014
ST305/ ST410
Lecture 23: Optimal Design an informal approach
Introduction
As we have seen, orthogonality is an important concept in design, and while it is very
useful, a lot of its appeal was that, in a pre-computer age, it made
DESIGNED EXPERIMENTS 2014
ST305 / ST410
Solutions to Worksheet 2 (week 7)
Exercise 1: Design scenarios (general)
For each of the following scenarios, write out an appropriate statistical model and the
usual assumptions. Define all terms and the ranges of
DESIGNED EXPERIMENTS 2014
ST305 / ST410
Worksheet 3 (week 9)
Exercise 1: Regression (Lecture 16)
The following data show the responses (%age of total calories obtained from complex
carbohydrates) for 20 male, insulin-dependent diabetics who had been on a
DESIGNED EXPERIMENTS 2014
ST305 / ST410
Solutions to Worksheet 1 (Week 2)
Exercise 1: Randomisation (Lecture 3)
There are three immediate ways that randomisation can be achieved in a simple experiment
with just two treatments, T and C. Suppose that the un
DESIGNED EXPERIMENTS 2014
ST305 / ST410
Solutions to Worksheet 3 (week 9)
Exercise 1: Regression (Lecture 16)
The following data show the responses (%age of total calories obtained from complex
carbohydrates) for 20 male, insulin-dependent diabetics who h
DESIGNED EXPERIMENTS 2014
ST305 / ST410
Worksheet 2 (week 7)
Exercise 1: Design scenarios (general)
For each of the following scenarios, write out an appropriate statistical model and the
usual assumptions. Define all terms and the ranges of the subscript
Lecture 13 Repeated measures
Repeated measures designs
are closely related to split-plot
and random effect designs in that
they allow for correlation within
each subject or random effect.
In repeat measurement
experiments, referred to as
Difference betwee
ST305 / ST410 DESIGNED EXPERIMENTS
Revision notes May 2014
The lecture notes you have are fairly comprehensive, and a thorough knowledge of
them should ensure success on May 31st! However, there is a lot of material there,
and some of you will not want to
ST305 / ST410
Designed Experiments
Lecture 19: Fractional Replication
Fractional replication
For a 26 experiment we would need 64 experimental
units for a single replicate. This would surely be
adequate if we were prepared to sacrifice 4th, 5th
and 6th or
ST305 / ST410
Designed Experiments
Lecture 22: Industrial Experimentation
- Robust Product (Parameter) Design
The sampling approach
For nearly all manufactured products limits are set
(sometimes by the receiving client, alternatively for
legal reasons) wi
DESIGNED EXPERIMENTS 2014
ST305 / ST410
Lecture 24: Repeated measures
Introduction
Repeated measures designs are closely related to split-plot and random effect
designs in that they allow for correlation within each subject or random effect. In
repeat mea
DESIGNED EXPERIMENTS 2014
ST305 / ST410
Lecture 22: Industrial Experimentation
Taguchi and Robust Parameter Design
Until quite recently statistical design methods were used
in agriculture and industry to assist experimenters to
maximise yields of a produc
ST305 / ST410
Designed Experiments
Lecture 3: Basic Concepts of
Experimental Design
Types of study
Observational studies
Sample surveys
Designed experiments
Comparative experiments
Treatments applied at different times / places will
almost certainly produ
ST305 / ST410
Designed Experiments
Lecture 20: Response Surfaces
In many industrial situations experimenters use
quantitative factors, and rather than simply
estimating means they seek to develop an
understanding of how the response varies with the
factor
DESIGNED EXPERIMENTS 2014
ST305 / ST410
Lecture 19: Fractional replication
Introduction
In looking at the factorial series experiments we have already considered the concept
of confounding, and the possibility of reducing the experiment size to a single
r
DESIGNED EXPERIMENTS 2014
ST305 / ST410
Lectures 20: Response surfaces
Introduction
In experimental situations we frequently use quantitative factors, and rather than
simply estimating the means it is often far more important to develop an understanding o
ST305 / ST410
Designed Experiments
Lecture 16: Regression and Matrix
Algebra
Regression and matrix algebra
Suppose we have a single response variable which we will
denote by y, and that we have m explanatory variables x1, x2,
, xm. We can model the depend