Chapter 1
Where Do Data Come From?
Chapter 1
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Thought Question 1
From a recent study, researchers
concluded that high levels of alcohol
consumption resulted in lower
graduation rates at colleges. How do
you think this study was carried out in
order to get these results? Do you think
the conclusion is correct? Is there a
more reasonable conclusion?
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Thought Question 2
It is popular knowledge that for similar jobs men earn more
money on average than women, and yet there are cases
where some women make more money than some men.
Therefore, to determine if men really do earn more, you would
need to sample many people of each sex. Suppose we also
want to know if, on average, men stay at their current jobs for
a longer time period than women. How could you go about
trying to determine this? Would it be sufficient to collect data
for one member of each sex?... two members of each sex?
What information about men’s and women’s measurements
would help you decide how many people to measure?
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Thought Question 3
In 1997, the Orlando Sentinel released the
results of a poll in which more than 90 percent of
those people who called in to the paper said that
Orlando’s NBA team, the Orlando Magic, should
not re-sign its center, Shaquille O'Neal, for the
amount of money he was asking. Based on this
poll, would you conclude that over 90% of
Orlando’s population felt that the team should
not re-sign Shaquille O’Neal?
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What is STATISTICS ?
Using
‘data’ to draw a conclusion
about something unknown.
Decision
making in the presence of
uncertainty.
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What Is “Data”?
(better: What are data?)
 Pieces
of
information.
 Numbers.
 The above are data
only if the
information has a
meaning attached.
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How Data are Obtained
 Observational Study
– Observes individuals and measures variables of
interest but does not attempt to influence the
responses
– Describes some group or situation
– Sample Surveys are a type of observational study
 Experiment
– Deliberately imposes some treatment on
individuals in order to observe their responses
– Studies whether the treatment causes change in
the response.
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Common Language
Individuals
 Population

– entire group of individuals about which we want information

Sampling Frame
– individuals that could possibly be selected for the sample (not
necessarily the same as the population)

Sample
– subset of individuals from which information is collected

Sample Survey
– type of observational study; data collected on a sample
 Census

Variable
– characteristic of an individual
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Population
individuals
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List of Individuals
Sampling Frame
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Sample
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Sample Survey
measurements
data
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Census
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Census
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List of Individuals
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Case Study
The Effect of Hypnosis
on the
Immune System
reported in Science News, Sept. 4, 1993, p. 153
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Case Study
The Effect of Hypnosis
on the
Immune System
Objective:
To determine if hypnosis strengthens the
disease-fighting capacity of immune cells.
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Case Study
 65
college students.
– 33 easily hypnotized
– 32 not easily hypnotized
 white
blood cell counts measured
 all students viewed a brief video about
the immune system.
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Case Study
 Students
randomly assigned to one of
three conditions
– subjects hypnotized, given mental exercise
– subjects relaxed in sensory deprivation
tank
– control group (no treatment)
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Case Study
 white
blood cell counts re-measured after one
week
 the two white blood cell counts are compared
for each group
 results
– hypnotized group showed larger jump in white
blood cells
– “easily hypnotized” group showed largest immune
enhancement
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Case Study
The Effect of Hypnosis
on the
Immune System
What is the population?
What is the sample?
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Case Study
The Effect of Hypnosis
on the
Immune System
What data were
collected?
 Easy
or difficult to
achieve hypnotic
trance
 Group assignment
 Pre-study white
blood cell count
 Post-study white
blood cell count
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Case Study
The Effect of Hypnosis
on the
Immune System
Is this an experiment
or
an observational study?
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Case Study
The Effect of Hypnosis
on the
Immune System
Does hypnosis and
mental exercise affect the
immune system?
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Case Study
Weight Gain Spells
Heart Risk for Women
“Weight, weight change, and coronary heart disease
in women.” W.C. Willett, et. al., vol. 273(6), Journal
of the American Medical Association, Feb. 8, 1995.
(Reported in Science News, Feb. 18, 1995, p. 108)
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Case Study
Weight Gain Spells
Heart Risk for Women
Objective:
To recommend a range of body mass index
(a function of weight and height) in terms of
coronary heart disease (CHD) risk in women.
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Case Study
 Study
started in 1976 with 115,818
women aged 30 to 55 years and without
a history of previous CHD.
 Each woman’s weight (body mass) was
determined
 Each woman was asked her weight at
age 18.
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Case Study
 The
cohort of women were followed for
14 years.
 The number of CHD (fatal and nonfatal)
cases were counted (1292 cases).
 Results were adjusted for other
variables.
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Case Study
 Results:
compare those who gained
less than 11 pounds (from age 18 to
current age) to the others.
– 11 to 17 lbs: 25% more likely to develop
heart disease
– 17 to 24 lbs: 64% more likely
– 24 to 44 lbs: 92% more likely
– more than 44 lbs: 165% more likely
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Case Study
Weight Gain Spells
Heart Risk for Women
What is the population?
What is the sample?
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Case Study
Weight Gain Spells
Heart Risk for Women
What data were
collected?
 Age
(in 1976)
 Weight in 1976
 Weight at age 18
 Incidence of coronary
heart disease
 Other: smoking, family
history, menopausal status,
post-menopausal hormone
use.
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Case Study
Weight Gain Spells
Heart Risk for Women
Is this an experiment
or
an observational study?
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Case Study
Weight Gain Spells
Heart Risk for Women
Does weight gain in
women increase their risk
for CHD?
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Key Concepts
 Knowing
about statistical methods will
have practical consequences in your
every day lives.
 Experiment versus Observational Study
 Common Terms
– Individuals, Population, Sampling Frame,
Sample, Sample Survey, Census, Variable
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