Transcript Section 4.3

Chapter 4
Gathering Data
Section 4.2
Good and Poor Ways to Sample
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Sampling Frame and Sampling Design
The sampling frame is the list of subjects in the population
from which the sample is taken, ideally it lists the entire
population of interest.
The sampling design determines how the sample is
selected.
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Simple Random Sampling, (SRS)
Random Sampling is the best way of obtaining a
sample that is representative of the population.
A simple random sample of ‘n’ subjects from a
population is one in which each possible sample of that
size has the same chance of being selected.
A simple random sample is often just called a random
sample. The “simple” adjective distinguishes this type of
sampling from more complex random sampling designs
presented in Section 4.4.
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SRS Example: Drawing Prize Winners
A campus club decides to raise money for a local charity by selling tickets.
* The Athletic Department has donated 2 pairs of football season tickets as
prizes.
* The group of 60 individuals who purchased tickets to the banquet
comprises the population.
Partial List of Possible Samples:
(1,2), (1,3), (1,4), . . . , (1,58), (1,59), (1,60)
(2,3), (2,4), . . . , (2,58), (2,59), (2,60)
Etc…
Questions:
1.
What is the chance that a particular sample of size 2 will be
drawn?
2.
Professor Shaffer is in attendance at the banquet and holds entry
number 1. What is the chance that her entry will be chosen?
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SRS: Table of Random Numbers
Table 4.1 A Portion of a Table of Random Numbers
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SUMMARY: Using Random Numbers to
select a SRS
To select a simple random sample:
 number the subjects in the sampling frame using
numbers of the same length (number of digits).
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
select numbers of that length from a table of
random numbers or using a random number
generator.

include in the sample those subjects having
numbers equal to the random numbers selected.
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Accuracy of the Results from Surveys
with Random Sampling
Sample surveys are commonly used to estimate
population percentages.
These estimates include a Margin of Error which tells
us how well the sample estimate predicts the population
percentage.
When a SRS of n subjects is used, the margin of error
is approximately equal to 1
n
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100%
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Accuracy of the Results from Surveys
with Random Sampling
A survey result states: “The margin of error is plus or
minus 3 percentage points”.
This means: “It is very likely that the reported sample
percentage is no more than 3% lower or 3% higher than
the population percentage”.
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SUMMARY: Types of Bias in Sample
Surveys
Bias: When certain outcomes will occur more often in the
sample than they do in the population.
 Sampling bias occurs from using nonrandom samples or
having undercoverage.
 Nonresponse bias occurs when some sampled subjects
cannot be reached or refuse to participate or fail to answer
some questions.
 Response bias occurs when the subject gives an incorrect
response (perhaps lying) or the way the interviewer asks the
questions (or wording of a question in print) is confusing or
misleading.
A Large Sample Does Not Guarantee An Unbiased Sample!
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Poor Ways to Sample
Convenience Sample: a type of survey sample that is
easy to obtain.
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
Unlikely to be representative of the population.

Often severe biases result from such a sample.

Results apply ONLY to the observed subjects.
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Poor Ways to Sample
Volunteer Sample: most common form of convenience
sample.
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
Subjects volunteer for the sample.

Volunteers do not tend to be representative of the
entire population.
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SUMMARY: Key Parts of a Sample Survey


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
Identify the population of all subjects of interest.
Construct a sampling frame which attempts to list all
subjects in the population.
Use a random sampling design to select n subjects from
the sampling frame.
Be cautious of sampling bias due to nonrandom samples
(such as volunteer samples) and sample undercoverage,
response bias from subjects not giving their true response
or from poorly worded questions, and nonresponse bias
from refusal of subjects to participate.
We can make inferences about the population of interest when
sample surveys that use random sampling are employed.
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