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Chapter 9

PSYC 2030 Chapter Notes - Chapter 9: Standard Deviation, Quota Sampling, Cable Television

Course Code
PSYC 2030
Krista Phillips

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Study Guide Chapter 9: Survey Research and Subject Recruitment
What are Opportunity and Probability Samples?
here we examine logic and limitations of the methods used to select research participants
Donald Rubin noted all studies lie on a continuum from irrelevant to relevant with respect to
answering a question
Randomized laboratory-type experiments that use opportunity samples of the first available
students in college settings have a restricted sample of participants but usually have a high
degree of control over the variables of interest
By contrast, researchers who do survey studies select potential respondents using special
sampling procedures in order to generalize their descriptive findsings to a specific larger pool (a
population) of people
If survey researchers used opprunity samples, spurious results and misleading generalizations
about the specific population of interest would seriousluy compromise scientific integrity of
their work
There is wide range of topics of interest to survey researchers
Pollsters use survey designs to map out some specified population’s opinions on important
societal issues such as the community’s fears of crime or its choice of political candidates
Similar methods are used sometimes in epidemiological research, forensic research, economic
research, and many other areas in which scientific surveys are conduction
When health officials wanted to find out about national trends in cases of tuberculosis
contracted on the job, they did scientific surveys of hospitals to count employees reported to
have TB
o As federal courts became inundated with mass torts involving asbestos cases, one
solution was to sample asbestos cases from the larger pool within a court’s jurisdiction
o Asses damages in randomly chosen cases from each of five disease categories were then
applied to each larger pool
o More recently, when researchers wanted to study the prevalence of psychological
resilience after a traumatic event they chose a probability sample of New Yorkers to
survey in the 6 months following 9/11
o Researchers reported resilience was present in two thirds of the sample and never fell
belwo one third even among highly exposed individuals with posttraumatic stress
Instead of trying to question every member of the population which is usually impossible, this
type of research focuses on a segment (sample) that is believed to be a typical of the population
How can researchers be certain that the segment is representative or typical of the population?
Ex. How can they be sure that a specific form of data from a sample is representative of a pop?
They might compare the sample with the most recent census data but it is well known that
census data are problemative because it is impossible to contact every member of the
Researchers who use a sample can enver be 100% sure of their generalizations
They can make reasonable guess by first developing an accurate sampling frame that defines the
target population and then relying on a carefully designed blueprint (sampling plan) to select
sample means of probability sampling
Probability sampling implies randomness enters into selection process at some stage so that
the laws of mathematical probability apply
Probability refers to the mathematical chance of an event’s occurring

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o Ex. Likelihood of getting “heads” when you flip a coin once (1 in 2) or getting a 2 when
you throw a die once (1 in 6)
Survey studies can take many different forms, all using sampling plans in whicih osme method of
probability sampling determines the random selection of the households or people to be
These plans enable the researcher to assume reaspnably but with no 100% guarantee of being
Practical problems may impose limits on representativeness of the sample
Even in most carefully conducted survey, not every household or person in the sample can be
reached and, of those who are actually contacted, not everyone will agree to be interview
In study of psychological resilience after the September 11, random digit-dialing approach was
used to contact members of the sample
When the number of completed and partial interviews was summed and this total was divided
by the sum of all numbers that were either eligible as residential phone numbers or of unkown
eligibility, the response rate was estimated to be 34%
What Is Meant By Bias and Instability in Survey Research?
Surey research done not only by private organziations, but by individual researchers owkring
alone or with ties to private organizations and in the US, at university based insitutes that can
implement face-to-face and telephone interviewing in national probability surveys
This research takes many different forms, all valid survey research is characterized by sampling
plans in wich every element or sampling unit in the population has a known nonzerio probability
of being selected at each draw
2 imporant statistical requirements of a probability sampling plan are a) the sample values are
unbiased and b) that there be stability in the samples
Unbiased values produced by sample must, on average, coincide with the true values of the
population but we can never actually be absolutely sure that this requirement has been met in
a given study unless we already know those values
Stability means there is not much variability (or spread) in the sample values
o it’s estimated by statistical procedures such as variance and the standard deviation
sampling theory is beautiful because it can be applied not only to individual respondents but
also to teams in a population of teams or to products on an assembly line, or to any other
specified population of animate or inanimate units
bias = systematic error
print page 166 there is a diagram and it’s above paragraph explains it
The Wine Taster
in manufacture of red wine, grapes are crushed and residue is put into huge cats in which
fermentation occurs
wine is then drawn off into barrels, where fermentation continues and product is periodficlly
sampled by the wine taster
wine taster needs to draw only a small sample in order to evaluate the quality of the wine in the
it’s the same in survey research: the more homogeneous the population, the smaller the sample
that needs to be drawn
Why Do We Not Know “For Sure” the Bias in Sampling?

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only way to know for sure about bias in sampling results is to examine every single member of
the popoulationa nd the sample at the same time the sampling is done if pattern replies in
same exactly matched pattern in population, we would know there was no sampling bias in
surveryed sample
practically speaking, if we already knew how everyone in a population was we wouldn’t be
doing a sample to help us study the population
it’s sometimes thought that election forecasting allows us to detect bias in sample because we
can compare predicted voting results with actual votes however problem in this case is that we
are comparing data obtained at one point in time with the results at another point in time
a well-designed and carefully implemented selection process involving probability sampling can
usually produce data that are remarkably close to the election results
polls = people can change their minds, they can be no shows, usually polls closer to election are
thought to be more accurate but still polls right up to day of voting disagree
How Is Simple Random Sampling Done?
Simple random sampling the basic prototype of probability sampling. The simple tells us that
the sample is selected from an undivided population, random means that the sample is to be
cjosen by a process that will give every unti in the specified population the same chance of being
selected at each draw
In order for this to occur, the selection of one unit must have no influence on the slection of the
other units
Assumption of random sampling: we have an understanding of the existence of all the units in
the population
Procedure: draw individuals one at a time until wehave as large a sample as we need
Process of selecting units might consist of computer drawing units at random, using a table of
random digits, or even spinning a roulette wheel or drawing well-mixed capsules from an urn.
Telephone interviewing: random digit dialing is sued to include households with unlisted
numbers area code and first three digits can be selected according to the geographic area of
interest, and then a computer program is used to randomly select the last four digits
Famous case showing hazards of inadequate randomization: Vietnam War, use of random
lottery to select conscripts for armed forces, birthdays out of urns, layers went: January, feb,
march, april, may even though urn was shaken for hours, the layers had formed and the
ballots came out in order
Use of table of random digits can help to avoid this
2250 digits list came from a million random digits that were generated by an electronic roulette
wheel programmed to produce a random frequency pulse every tiny fraction of a second
A computer then counted the frequency of 0s, 1s, 2s, and so on on assumption that an
impartial probability method would produce an approximately equal number of 0s, 1,s 2,s and
so on in the overall table of a million random digits this equality was confirmed
To see how you might use this table if you wanted to do random selection in a survey, imagine
you want to interview 10 men and 10 women individually after choosing them at random from a
list of 96 men and 99 women
You would begin by numbering the population of men consecutively from 01 to 96 and the
population of women from 01 to 00
You are not ready to use the random digits to do so, you can put your finger blindly on a
starting position
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