Transcript Ch 1.5 - San Diego Mesa College

Design of Experiments
Created by Tom Wegleitner, Centreville, Virginia
Edited by Olga Pilipets, San Diego, California
Copyright © 2007 Pearson
Education, Inc Publishing as
Pearson Addison-Wesley.
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Key Concepts
 Sample data must be collected in an
appropriate way, such as through a
process of random selection.
 If sample data are not collected in
an appropriate way, the data may
be so completely useless that no
amount of statistical torturing
can salvage them.
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observing and measuring specific
characteristics of objects without
modifying them in any way.
Example: Gallop poll ( observing
through interviews)
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
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In 1855 John Snow discovered that cholera is
a waterborne infectious disease. Snow was a
physician in London.
Some 20 years before Koch and Pasteur laid
the foundations of modern microbiology
By observing the course of the disease, he
concluded that cholera was caused by a living
organism, which entered the body with water
or food, multiplied in the body, and made the
body expel water containing copies of the
organism.
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Snow explained the lag between infection and
disease—a matter of hours or days—as the time
needed for the infectious agent to multiply in the
body of the victim (poisons work instantly)
 cholera spread along the tracks of human
commerce.
 Furthermore, when a ship entered a port where
cholera was prevalent, sailors contracted the
disease only when they came into contact with
residents of the port.
These facts were easily explained if cholera was an
infectious disease,

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 apply
some treatment and
then observe its effects on the
subjects
 Example: In the experiment
designed to test the Salk vaccine,
200,000 children were given the
actual Salk vaccine and 200,000 other
children were given a placebo.
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
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Cross sectional study
data are observed, measured, and collected at
one point in time
Retrospective (or case control) study
data are collected from the past by going
back in time
Prospective (or longitudinal or cohort) study
data are collected in the future from groups
(called cohorts) sharing common factors
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Replication and Sample Size
 Sample Size
use a sample size that is large enough to see
the true nature of any effects
obtain that sample using an appropriate
method, such as one based on randomness
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Definitions
 Random Sample
members of the population are selected in
such a way that each individual member has
an equal chance of being selected
Simple Random Sample
(of size n)
subjects selected in such a way that every
possible sample of the same size n has the
same chance of being chosen
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Random Sampling
selection so that each
individual member has an
equal chance of being selected
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Systematic Sampling
Select some starting point and then
select every k th element in the population
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Convenience Sampling
use results that are easy to get
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Stratified Sampling
subdivide the population into at
least two different subgroups that share the same
characteristics, then draw a sample from each
subgroup (or stratum)
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Cluster Sampling
divide the population into sections
(or clusters); randomly select some of those clusters;
choose all members from selected clusters
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Methods of Sampling - Summary
 Random
 Systematic
 Convenience
 Stratified
 Cluster
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Definitions

Sampling error
the difference between a sample result and
the true population result; such an error
results from chance sample fluctuations

Nonsampling error
sample data incorrectly collected, recorded, or
analyzed (such as by selecting a biased
sample, using a defective instrument, or
copying the data incorrectly)
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Recap
In this section we have looked at:
 Types of studies and experiments
 Randomization
 Types of sampling
 Sampling errors
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#8 p. 31
Cruise ship passengers are given magnetic
bracelets, which they agree to wear in an
attempt to eliminate or diminish the effects
of motion sickness.
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#10 p.31
A researcher from Johns Hopkins University
obtains data about the effects of alcohol on
driving by examining car crash reports from
the past five years.
retrospective
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#12 p.31
An economist collects income data by selecting
and interviewing subjects now, then going
back in time to see if they had the wisdom to
take a statistics course between the years of
1980 and 2008.
retrospective
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#22 p.32
A market researcher has partitioned all
California residents into categories of
unemployed, employed full time and
employed part time. She is surveying 50
people from each category.
Stratified
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#16 p.32
An engineering student measures the strength
of fingers used to push buttons by testing
family members.
Convenience
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#28 p.33
A researcher for the Orange County Department of Motor
Vehicles plans to test a new online driver registration system
by using a sample consisting of 20 randomly selected men
and 20 randomly selected women. (Orange County has an
equal number of male and female drivers). Does this
sampling plan result in a random sample? A simple random
sample?
Yes, no. All drivers have the same chance of being selected,
but some samples (such as those with 21 men and 19
women) have no chance of being chosen.
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