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CHAPTER 3 – EXPERIMENTAL AND SAMPLING DESIGN
Overview of how to answer a research question:
1.
Pick a specific question you want to answer.
2.
Decide on your population.
3.
Select a sampling design and gather your sample.
The choices for sampling designs for this class are:
•
voluntary response (the only one not random, not the best)
•
simple random sample
•
stratified random sample
•
multistage sample
•
catchandrelease sample
4.
Decide whether to conduct an observational study or an experiment. If observational study, just state
the sampling design. If experiment, the choices for experimental designs for this class are:
•
completely randomized design
•
block design
•
matched pairs
5.
Choose your response variable and your explanatory variables.
Decide on your treatments (for
experiments).
6.
Collect the data.
7.
Analyze your data using either exploratory data analysis (looking for trends/relationships in the actual
data) or formal statistical inference (answering statistical questions with a known degree of
confidence).
8.
State your conclusions.
What can go wrong?
•
Bias (response bias, nonresponse, undercoverage)
•
Variability
•
Poor experimental design (not using a control, not randomizing, not replicating)
•
Other (poor choice of sampling design, date of survey)
Think about why your variables are related.
Causation is not the same thing as association!
Is the
relationship between your variables based on:
♦
Causation
♦
Confounding
♦
Common response
Principles of Ethical Experiments
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Planned studies should be reviewed by a board to protect subjects from harm.
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All subjects must give their informed consent before data are collected.
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All individual data must be kept confidential.
Only summaries can be made public.
(Anonymity is
not the same as confidentiality.)
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VOCABULARY
Population
:
The entire group of units or
individuals about which we desire information.
Sample
:
The part of the population selected to
be measured or observed in order to gather data
for analysis.
Census
:
An attempt to contact every individual
in the entire population.
Response Variable
: Variable we are interested in studying.
Unit
:
An individual person, animal or object upon which the response variable is measured.
Units are
called “individuals” when they refer to people.
EXAMPLE
A forester is interested in determining the total number of trees that are planted on tree farms in Montana.
The forester believes the number of trees varies with the size of the tree farm.
He divides all such farms
into four classes depending on their size.
From each class, he selects a sample of 15 farms.
He counts and
records the total number of trees for each of the selected tree farms.
Unit:
Population:
Sample:
Response variable:
MAJOR IDEA
We are interested in one or more variables associated with a population of units.
Because it is impossible
or too expensive to measure the variables of interest on all the units in the population, we only measure the
variables on a subset or a sample of units.
We use the sample to draw conclusions about the population.
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 Spring '08
 Staff
 random sampling designs

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