Chapter 5 : Producing Data
AP Statistics Standards
II. Sampling and
Experimentation: Planning and conducting a study (10% –15%)
A. Overview of methods of data
collection
- Census
- Sample survey
- Experiment
- Observational study
B. Planning and conducting surveys
- Characteristics of a well-designed
and well-conducted survey
- Populations, samples, and random
selection
- Sources of bias in sampling and surveys
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Sampling methods, including
simple random sampling, stratified
random sampling, and cluster sampling
C. Planning and conducting experiments
- Characteristics of a
well-designed and well-conducted experiment
- Treatments, control groups,
experimental units, random assignments,
and replication
- Sources of bias and
confounding, including placebo effect and blinding
- Completely randomized design
- Randomized block design, including
matched pairs design
D. Generalizability of results from
observational studies, experimental studies,
and surveys
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Objectives |
| Essential Question:
Can bad data be corrected with
good statistical analysis? |
Designing Samples
- Distinguish between population and samples and tell
which one forms the basis of statistics.
- Define bias (p273).
- Define voluntary response and convenience
sampling. Explain why they
invariably
produces biased results.
- Identify when confounding is present.
- Explain why confounding and bias make
statistical inference impossible. (Inference implies that there is no other
reasonable explanation for the data.)
- State the key difference between a statistical study
and a non-statistical study. Proper sampling technique
- State the two basic forms of statistical studies.
- Observational / Survey
- Experiment
- Describe an SRS and state what it seeks to eliminate.
(With a sample size of n, every set of n individuals has an
equal chance of being chosen from the population.)
- State how an SRS is formed.
- Use a table of random digits to create an SRS.
Seed a random number generator (such as a table) only once.
- State the problem which the magic word "randomization"
solves.
- State the primary weakness of an SRS.
- Variability from study to study.
Occasionally a random sample will select a single type
of subject instead of a representative sample. For example, a random sample
of the United States could end up being 100 % motor cycle gang members or
100% kindergarten teachers. Obviously they will answer questions
differently.
Homefun : prob. 5.1, 5.3,
5.5,5.7
Relevance: Proper sampling is the
foundation statistics rests on.
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Activities |
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- Lesson 1
- Key Concept: Designing systematic, statistically sound ways to
collect data
- Purpose:
Interactive Discussion:
Objectives
Seat Work: generate random
numbers using a random number table.
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| Essential Question:
What is the difference between
preventing variability and preventing bias in a statistical study? |
- Describe the key method for preventing
variability
in observational studies and surveys. Stratification
- Describe how a multistage sample design is used
for preventing variability.
- Describe 4 ways to do a perfectly good job of sampling and still get worthless results
(p. 281).
- Under coverage - Leaving groups
out of the sample selection process. Homeless people are particularly
difficult to reach since they typically have neither phone numbers or
addresses.
- Non response - Mr. Rogers
Syndrome (he doesn't do surveys)
- Response Bias - a) Intimidating
interviewer b) Intimidating question
- Wording Effects - Asking
the wrong question or biasing the result.
Homefun: 5.11, 5.13, 5.15,
5.17
Relevance: Our democratic political
system depends on properly conducted sampling. It is the way politicians can
judge how people would vote on an issue if given the chance. A politician can
then choose to follow the will of the majority or attempt to educate the
majority to a more correct point of view.
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- Lesson 2
- Key Concept:
Variability and bias--surveys
- Purpose:
How to prevent the above in surveys
Interactive Discussion:
Objectives
Group Work:
Correctly design a survey for Southside high
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| Essential Question:
Which is more reliable a
census or a sample? |
- State the key advantage of a census over a
sample.
- no sampling errors.
Otherwise they both suffer from the same
kind of problems.
- Explain the key disadvantages of a census vs. a
survey.
- slow--conditions can change before the
census is complete, for example during elections
- expensive
- State the problems common to both samples and
surveys along with potential solutions.
- Under coverage use a variety of
techniques to reach the sample group.
- Non response:
resurvey non-responders often with a different contact method such as a
phone call or personal interview.
- Response Bias:
carefully select and train interviewers.
- Wording Effects: use focus groups or
preliminary surveys to
screen questions. Ask the same question in more than one
way and test to see if the answers differ..
Relevance: Taking a census
every 10 years is mandated by the U.S. Constitution. It is an
important factor in our political system because it determines things
such as the number of congressional representstives. It also
determines many types of funding.
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| Essential Question:
Why are experiments considered
more convincing than observational studies? |
Experiments
- Correctly use the following terms:
- Experimental unit/subject
- Treatment
- Factor/level
- Placebo effect
- Control group
- Completely randomized design
- State the magic word which is used in all experiments
and state why and how it is used. Hint: remember the "R".
- Explain the conditions which make an effect
statistically significant (p. 296).
- Be as one with the three basic principles of
experimental design.
- Control - effects of lurking
variables
- Randomization - prevents sampling
bias. The subjects in treatment groups are chosen at random. The treatment a
particular group gets is chosen by a random process.
- Replication - collect numerous data
points
- Describe how
double blind testing is used.
- Discuss the ethical considerations of double blind
testing.
- Correctly use
blocking in an experimental design.
- identify key lurking variable(s)
- set up the blocks as homogeneous as possible with
respect to key lurking variables
- randomize the treatments: select different treatment
groups randomly from within the block.
- Explain why blocking reduces study to study variability.
- it
helps insure that lurking variables affect all treatment groups equally.
Hence the effects cancel out.
- State the problem that blocking does not solve.
- Set up matched pairs designs.
Homefun: 5.25,
5.41, 5.47, 5.55
Relevance: Double blind testing is
the required standard for drug approval in the U.S. Any benefits claimed for a
drug, supplement or remedy that has not been double blind tested have to be
viewed with great skepticism. Example: facilitated communication with autistic
people.
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- Lesson 3
- Key Concept:
Variability and bias--experiments
- Purpose:
How to prevent the above in experiments.
Interactive Discussion:
Objectives
Group Work:
Correctly design an experiment for the AP test fish tank example.
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