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Statistics 528  Lecture 11
1
Statistics 528  Lecture 11
Prof. Kate Calder
1
Big Picture
Collect Data (experiment or sample survey)
Exploratory Data Analysis
Formal Statistical Inference
Statistics 528  Lecture 11
Prof. Kate Calder
2
•
We need to collect trustworthy data and be able to judge the quality of
data produced by others in order to be able to do formal statistical
inference (generalize results in samples).
•
We do not want to base conclusions or inferences on
anecdotal
evidence
.
•
Sources of available data:
–
Statistical Abstract of the United States
– Government databases
– Internet
Statistics 528  Lecture 11
Prof. Kate Calder
3
Observation vs. Experiment
•
An
observational study
observes individuals and measures variables
of interest but does not attempt to influence the individuals’ responses.
•
An
experiment
imposes some treatment on individuals in order to
observe their responses.
Statistics 528  Lecture 11
Prof. Kate Calder
4
Samples
•
A
population
is the collection of individuals (do not have to be
people) we are interested in studying.
•
A
sample
is a subset of the population.
•
If we can measure every individual in our population we have
census.
Statistics 528  Lecture 11
Prof. Kate Calder
5
Example:
Some people believe that exercise raises the body’s metabolic
rate for as long as 12 to 24 hours enabling us to continue to burn off fat
after our workout has ended. In a study of this effect, subjects were
asked to walk briskly on a treadmill for several hours. Their metabolic
rates were measured before and 12 hours after the exercise.
Question:
Was this study an experiment? Why or why not?
Question:
What are the explanatory and response variables?
Statistics 528  Lecture 11
Prof. Kate Calder
6
Design of Experiments
Terminology:
•
The individuals on which the experiment is done are called the
experimental units
. When the units are human beings, they are called
subjects
.
•
A specific experimental condition applied to the units is called a
treatment
.
•
The explanatory variables that you are think may explain the effect of
the treatments are called
factors
. The specific values of each of the
factors are called
levels
.
•
An
experimental design
describes how the treatments are assigned to
the experimental units.
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View Full Document Statistics 528  Lecture 11
2
Statistics 528  Lecture 11
Prof. Kate Calder
7
Example:
What are the effects of repeated exposure to an advertising
message? The answer depends both on the length of the ad and on how
often it is repeated. An experiment is conducted with undergrad
students of OSU to investigate this question. All subjects viewed a 60
minute episode of a television show that included ads for a new ice
cream. Some subjects saw a 30second ad; others, a 90second version.
The same ad was repeated 1, 3, or 5 times during the program. After
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This note was uploaded on 07/26/2011 for the course STA 528 taught by Professor Calder during the Winter '09 term at Ohio State.
 Winter '09
 Calder
 Statistics

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