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Chapter 5: Producing Data
5.1 Designing Samples (pp. 269-285)
1. What is an observational study? An observational study observes individuals and measures
variables of interest but does not attempt to influence the responses.
2. What is an experiment? An experiment deliberately imposes some treatment on individuals in
order to observe their responses.
3. Which of these can show a causal relationship? An experiment can show a causal relationship.
4. Explain the difference between a population and a sample. The population is the entire group
of individuals that we want information about. A sample is a part of the population that we
actually examine in order to gather information.
5. Explain the difference between sampling and a census. Sampling involves studying a part in
order to gain information about the whole. A census attempts to contact every individual in
the entire population.
6. Why are voluntary response samples unreliable? A voluntary responses sample consists of
people who choose themselves by responding to a general appeal. Voluntary response
samples are biased because people with strong opinions, especially negative opinions, are
most likely to respond.
7. Why might convenience sampling be unreliable? A convenience sample is chosen for
convenience. Convenience sampling chooses the individuals who are easiest to reach. This
sample may be unreliable because the collection of individuals may not be representative of
the entire population
8. What is a biased study? The design of a study is biased if it systematically favors certain
outcomes.
9. What is meant by the design of a sample? The design of a sample refers to the method used to
choose the sample from the population.
10. Define simple random sample. A simple random sample (SRS) of size n consists of n
individuals from the population chosen in such a way that every set of n individuals has an
equal chance to be the sample actually selected.
11. What two properties of a table of random digits make it a good choice for creating a simple
random sample? A table of random digits is a long string of the digits 0, 1, 2, 3, 4, 5, 6, 7, 8,
9, with these two properties:
1) Each entry in the table is equally likely to be any of the 10 digits 0 through 9.
2) The entries are independent of each other. That is, knowledge of one part of the table gives
no information about any other part.
12. What are the two steps for choosing a SRS?
Step 1: Label. Assign a numerical label to every individual in the population.
Step 2: Table. Use Table B (or calculator) to select labels at random.
13. What is a probability sample? A probability sample is a sample chosen by chance. We
must know what samples are possible and what chance, or probability, each possible sample
has.
14. What is a stratified random sample? To select a stratified random sample, first divide the
population into groups of similar individuals, called strata. Then choose a separate SRS in
each stratum and combine these SRSs to form the full sample.
15. Give an example of undercoverage in a sample. Undercoverage occurs when some groups
in the population are left out of the process of choosing the sample.
16. Give an example of nonresponse bias in a sample. Nonresponse bias occurs when an
individual chosen for the sample can’t be contacted or does not cooperate.
17. How can the wording of questions cause bias in a sample? Give an example. Confusing or
leading questions can introduce strong bias, and even minor changes in wording can change a
survey’s outcomes. EX: “Some cell phone users have developed brain cancer. Should all cell
phones come with a warning label explaining the danger of using cell phones?”
18. Which gives more accurate results, large samples or small samples? Larger random
samples give moe accurate results than smaller samples.
5.2
Designing Experiments (pp. 290-306)
1. Explain the difference between experimental units and subjects. The experimental units are the
individuals on which the experiment is done. When the units are human beings they are
called subjects.
2. Define treatment. A treatment is the specific experimental condition applied to the units.
3. Give an example of at least two levels of a factor in an experiment. Two factors could be
giving beta carotene and giving aspirin to subjects in an experiment.
4. Describe the placebo effect. A placebo is a dummy treatment. Many patients respond favorably
to any treatment, even a placebo. This may be due to trust in the doctor and expectations of a
cure, or simply to the fact that medical conditions often improve without treatment.
Favorable response to a dummy treatment is the placebo effect.
5. What is the significance of using a control group? The group of patients who receive the
dummy treatment or placebo is the control group. Use of a control group enables us to
control the effects of outside variables on the outcome. Control is the first basic principle of
statistical design of experiments.
6. Define randomization. Randomization is the use of chance to divide experimental units into
groups. It is an essential ingredient for good experimental design. When all experimental
units are allocated at random among all treatments, the experimental design is completely
randomized.
7. Define statistically significant. An effect is statistically significant if an observed effect is so
large that it would rarely occur by chance.
8. What are the advantages of a double-blind study? In a double-blind experiment, neither the
subjects not the people who have contact with them know which treatment a subject
received.
9. Describe a block design. A block is a group of experimental units or subjects that are known
before the experiment to be similar in some way that is expected to affect the response to the
treatments. In a block design, the random assignment of units to treatments is carried out
separately within each block.
10. Describe a matched pairs design. Matched pairs are a common form of blocking for
comparing just two treatments. In some matched pairs designs, each subject receives both
treatments in a random order. In others, the subjects are matched as closely as possible, and
one subject in each pair receives each treatment. Blocks allow us to draw separate
conclusions about each block.
11. What is the most serious potential weakness of experiments? The most serious potential
weakness of experiments is lack of realism. The subjects or treatments or setting of an
experiment may not realistically duplicate the conditions we really want to study.
12. What are the basic principles of statistical design for experiments? The three basic
principles of statistical design are:
Control the effects of lurking variables on the response, most simply by comparing two or
more treatments.
Randomize – use impersonal chance to assign experimental units to treatments.
Replicate each treatment on many units to reduce chance variation in the results.
5.3
Simulating Experiments (pp. 309-316)
1. What is simulation? Simulation is the imitation of chance behavior, based on a model that
accurately reflects the experiment under consideration.
2. List the five steps for conducting a simulation:
Step 1: State the problem or describe the experiment
Step 2: State the assumptions.
Step 3: Assign digits to represent outcomes.
Step 4: Simulate many repetitions.
Step 5: State your conclusions.