Sec. 5.1 ~ Designing Samples
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Our goal in choosing a sample is to obtain a picture of the population that is disturbed as little as possible by the
act of gathering information.
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Sample surveys are one kind of observational study.
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In other settings, we gather data from an experiment.
Observation vs. Experiment
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An observational study observes individuals and measures variables of interest but does not attempt to
influence the responses.
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An experiment, on the other hand, deliberately imposes some treatment on individuals in order to observe their
responses.
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Both have important roles depending on the situation and the questions to be answered.
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See example 5.1 on p.270
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Observational studies of the effect of one variable on another often fail because the explanatory variable is
confounded with lurking variables.
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In some situations, it may not be possible to observe individuals directly or to perform an experiment. In other
cases, it may be logistically difficult or simply inconvenient.
Population and Sample
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The entire group of individuals that we want information about is called the population.
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A sample is a part of the population that we actually examine in order to gather information.
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Sampling involves studying __________________in order to ____________________________________
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A census attempts to contact every individual in the entire population.
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The design of a sample refers to the method used to choose the sample from the population.
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Poor sample design can produce misleading conclusions.
Voluntary Response Sample
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A voluntary response sample consists of people who choose themselves by responding to a general appeal.
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Voluntary response samples are ________________because people with____________________,
especially________________________, are most likely to respond.
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See example 5.2 on p.272
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Another type of bad sampling is convenience sampling, which chooses the individuals easiest to reach.
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See example 5.3 on p.272
Bias
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The design of a study is biased if it systematically favors certain outcomes.
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Choosing a sample by ______________________ attacks bias by ______________________________________
to be chosen.
Simple Random Sampling
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A simple random sample (SRS) of size n consists of __________________________________ chosen in such a
way that every set of n individuals ___________________________________________
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An SRS not only gives each ____________________ an equal chance to be chosen, (thus avoiding bias in the
choice) but also gives ______________________________an equal chance to be chosen.
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Not all random samples are simple random samples:
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If I have 10 names in a hat, the probability of any one name being drawn is 1 out of 10. After the first
name is drawn, there are nine names left in the hat changing the probability of anyone being selected as
the second name to be 1 out of 9. Since different names have different probabilities depending on the
sequence in which the drawing is done, the resulting sample will not be a simple random sample.
Random Digits
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A table of random digits is a long string of the digits 0,1,2,3,4,5,6,7,8,9 with the following two properties:
1. Each entry in the table is equally likely to be any of the 10 digits 0 through 9.
2. The entries ___________________________________. That is, knowledge of one part of the table gives
no information about any other part.
*Table B (in the back of your textbook) is a Random Digit Table
Choose an SRS in two steps:
1. Table: Use Table B to select labels at random.
2. Label: Assign a numerical label to every individual in the population.
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See example 5.4 on p.276
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A probability sample is a sample _________________________ We must know
___________________________and what ___________________________each possible sample has.
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Systematic sampling is a type of probability sampling in which the sampling starts by selecting an element
from the list at random and then every kth element in the frame is selected to be part of the sample.
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The use of chance to select the sample is the essential principal of statistical sampling.
Stratified Random Sample
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To select a stratified random sample, first ______________________________________________________
Then choose a separate ____________________________and combine these ____________________________
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This method is usually used for sampling from large populations spread out over a wide area.
Cluster Sampling
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With cluster sampling, the researcher _______________________________________________________
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Then, an __________________________ is selected from the population and ____________________________
o
For example, if a researcher is studying the attitudes of Catholic Church members surrounding the
recent exposure of sex scandals in the Catholic Church, he or she might first sample a list of Catholic
churches across the country. Let’s say that the researcher selected 50 Catholic Churches across the
United States. He or she would then survey all church members from those 50 churches.
Multistage Sampling
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
A typical example of multistage sampling is Current Population Survey Sampling Design, which is conducted
as follows:
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Stage 1: Divide the United States into 2007 geographical areas called Primary Sampling Units.
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Stage 2: Divide each PSU selected into smaller areas called “neighborhoods” using ethnic and
other information and take a stratified sample of neighborhood.
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Stage 3: Sort the housing units in each neighborhood into clusters of four nearby units.
Interview the households in a random sample of these clusters.
This method saves time and money.
Cautions about Sample Surverys
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We need a complete and accurate list of the population.
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Undercoverage occurs when some groups in the population are left out of the process of choosing the sample.
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See example 5.6 on p.281
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Nonresponse occurs when an individual chosen for the sample can’t be contacted or does not cooperate.
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Response bias is_______________________________ , especially if asked about illegal or unpopular behaviors.
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An interviewer whose attitude suggests that some answers are more desirable than others will get these
answers more often.
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The wording of questions is the most important influence on the answers given to a sample survey.
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See example 5.7 on p.282
Inference about the Population
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Using chance to choose a sample eliminates ______________ in the actual selection of the sample.
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Because we deliberately use chance, the results obey the laws of probability that govern chance behavior.
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Larger random samples give more accurate results than smaller samples.