sampling in survey methodology
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Sampling in Survey Methodology
Skerdi Zahaj
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Are Americans romantic?
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A survey conducted specifically to compare findingsto a French survey regarding love and relationships
(Schwartz, 2010).
Are they romantic compared to the French, who arerenowned for their passion for passion?
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(Schwartz, 2010)
In LoveCan true love exist without a radiant
sex life?
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If you want to know what people are doing, observe
them!
If you want to know what people are thinking, askthem!
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Survey
Survey research involves selecting a sample (or samples)
and using a predetermined set of questions.
When a representative sample of people is asked the same
set of questions, we can describe the attitudes of thepopulation from which the sample was drawn.
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If the human population on Earth was homogenous incharacteristics, how many people would an alien need toabduct in order to understand what humans were like?
If all members of a population were identical, thepopulation is considered to be homogenous.
That is, the characteristics of any one individual in thepopulation would be the same as the characteristics of anyother individual (little or no variation among individuals)
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When individual members of a population are differentfrom each other, the population is considered to be
heterogeneous (having significant variation amongindividuals).
How does this change an aliens abduction scheme to find
out more about humans?
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In order to describe a heterogeneous population,
observations of multiple individuals are needed toaccount for all possible characteristics that may
exist.
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Population
Assume youve decided your research question is bestanswered using a survey, and youve determined the
population of interest for your survey.
The next step is to decide who should respond to yoursurvey questions.
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Population
Is any well-defined set of unit of analysis
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Population lists
Countr
yorst
ate
Country or state
Work
ingin
aorgan
Working in a organization
Se
tofco
untr
ie
Set of countries
Cor
poratio
ns
Corporations
Ev
ents
Events
Magaz
i
Magazine articles
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Population
Population = People
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Sample
Any subset ofunits collected in some manner from population
Samplingis the process of selecting a small number of elementsfrom a larger defined target group of elements such that theinformation gathered from the small group will allow judgments to
be made about the larger groups
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The Language of Sampling
Sample frame: a specific list that closely approximates allelements in the populationfrom this the researcher selects
units to create the study sample
Sample frame: The particular population from which asample is actually drown
Sample element: a case or a single unit that is selected froma population and measured in some waythe basis ofanalysis (e.g., an person, thing, specific time, etc.).
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Basics of Sampling Theory
Population
Sampling frame
Sample
Element
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Basics of Sampling Theory
All students on campus
Registrars list of all students
100 students
Student
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What is Sampling?Population
SampleSamplingFrame
Sampling Process
What youwant to talk
about
What youactually
observe inthe data
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Conceptual ModelUniverse
Population
Sample Population
Sample Frame
Elements
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Population or Sample
Populations, not samples, are of primary interest
The power of samples to describe the larger population is
based on the assumption that survey responses in a sample canbe applied to the population from which the sample wasdrawn.
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Why do researchers select a sampleand do not study the population?
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We select the sample
Time Money
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Population or sample
Advantages
Disavantages
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If the sample is selected properly the information may beused to make interference about the whole population.
Sampling arises whenever a researcher takes measurementson a subset of population, however defined, covered by thehypothesis being investigated
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The major threat to representativeness is bias
Biased sample is one in which the distribution ofcharacteristics in the sample is systematically different from
the target population.
A sample of 100 adults that included 80 women and 20 menwould likely be biased if the population were 60% female
and 40% male
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Biased sample
Selection biasprocedures used to selectthe sample result in theoverrepresentation of somesegment of the populationor, conversely, in the
exclusion orunderrepresentation of asignificant segment.
Exit Polls
exit polls are used to surveypeoples attitudes.
demographic characteristics
such as age, race, education,and income of votersinterviewed in exit pollsdiffer from characteristicsof the population.
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Literary Digest poll 1936
Alf. M Landon Franklin D. Roosevelt
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Overrepresented wealthy individuals
The sample frame was selected from :
1. Telephone numbers
2. Automobile ownership
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Types of samples
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We have a problem.
Two student researchers have been asked to do a survey todetermine the attitudes of students toward fraternities and
sororities on campus.
There are 3,200 students in the school. About 25% of thestudents belong to the Greek organizations and 75% do not.
The two student researchers disagree about what samplingplan is best for the study. One researcher thinks they shoulddraw a stratified random sample of200 students: 100 fromamong those students who belong to Greek organizationsand 100 from among the independent students. The secondresearcher thinks they should draw one simple randomsample of 100 students from the campus as a whole.
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The problems
A potentially serious flaw of this plan is that the overallsample would not represent the proportions of Greeks and
independents in the population (25% and 75%,respectively). This would result in a biased sample becauseGreeks would be systematically overrepresented in thesurvey.
The second student researcher is proposing a simplerandom sample of 100 students from the campus
population. While this is likely to lead to a morerepresentative sample, it will probably result in too few
respondents in the Greek category (wed expect about 25Greeks) to adequately represent their viewpoint.
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The solution
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Here it is
A preferred sampling plan would use a stratifiedrandom sample in which the sample sizes for
Greeks and independents are proportional to thepopulation values. With 200 students in the sample,
you would select 150 students from the samplingframe of independent students and 50 students
from the sampling frame of Greek students
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Types of sampling
P
rob
abi
lit
y
Probability sample
Non
pro
b
Nonprobability sample
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Click icon to add picture
Probability sample
Click icon to add picture
Is a sample for which each element in thetotal population has a known probability
of being included in the sample.
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Click icon to add picture
Nonprobability sample
Click icon to add picture
Is a sample for which each element in the totalpopulation has a known probability of beingincluded in the sample.
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Probability sample
Sim
pler
andom
sam
p
l
Simple random sample
Syst
ematic
sam
pl
e
Systematic samples
S
tratif
iedsa
m
Stratified samples
Clu
sters
a
Cluster samples
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Probability sampling is far superior to
nonprobability sampling in ensuring
that selected samples represent the
population.
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Simple random
Each element and combination of elements has an equal chance ofbeing selected.
A list of all elements in the population must be available and a methodof selecting those elements must be used that ensures that each elementhas an equal chance of being selected.
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Random lottery
Write every-day of year on separate slips of paper
Placing the slips in separate capsules
Putting all the capsules in a barrel
After turning the drum, days would be drawn randomly
On December 1, 1969 the dates were drawn one afteranother and given a number
The firs date 14 September was given number 1
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Problems
Anyone with a number 200 or would probably not be called
If birthday was early on, there was a good chance that hewould have serve
Randomness supposedly ensured the systems fairness
Was noticed that people with low numbers tended to beborn in the latter months
The capsules may have been insufficiently mixed
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The steps of Random Samples
Assigni
nganu
mbert
o
Assigning a number to each element in a sample frame
Usi
ngara
ndom
n
Using a random numbertable
Sele
ctasa
m
Select a sample of numbers
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The steps of Random Samples
Po
pulati
on
Population
Dra
w
Draw
Star
t
Start
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By the lot method
Elements are drawn outrandomly until the
desired sample size hasbeen reached.
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Third level Fourth level
Fifth level
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In Simple RandomSampling
The gap, or period between successive elements is
random, uneven, has no particular pattern
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Simple random sampling requires a
list of the members of population
The conclusion
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Systematic Sample
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Systematic Sample
Elements are selectedfrom a list at
predetermined intervals
Elements are chosen
from the listsystematically ratherthan randomly
Everyxth element onthe list is selected
This number is calledsampling interval
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In SystematicSamplingGaps between elements are equal andConstant There is periodicity.
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Problem????
We want to draw a sample of 100 names from a list of5000 students attending a college.
We would go through the list andselect every fiftieth students
We would select a random start
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Systematic sampling
We deal with a long listof population elements
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Disadvantages
Elements of the listhave been ranked
according to acharacteristic
Students grades
People income
.
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Disadvantages
List contains a patternthat corresponds to
the sampling interval
Attitudes of children
from large families
Sampling interval is 5
Families included in thelist have 5 children
We will sample all thechildren who were in
the same position
Birth Order
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Stratified sample
Probability sample inwhich elements sharing
one or morecharacteristics aregrouped
Divide the population by certaincharacteristics into homogeneoussubgroups (strata) (e.g., UI PhD
students, Masters Students,Bachelors students).
Elements within each strataare homogeneous, but areheterogeneous across strata.
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A simple random or a systematic sample is taken from each stratarelative to the proportion of that stratum to each of the others.
Stratified sample
Proportionate (Each stratum is representedin proportion to its size in the population)
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POPULATION
STRATA 1STRATA2
n = 1000; SE = 10%
n= 500; SE=7.5% n = 500; SE=7.5%
Equal intensity
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POPULATION
STRATA 1
STRATA 2
n =1000, SE = 10%
n = 600SE=5.0%
n =400SE=7.5%
Proportional to size
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Sample equal intensity vs.?proportional to size ?
What do you want to do? Describe the population,ordescribe each strata?
1. Equal intensity
2. Proportional size
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Stratified sample
Characteristics that are expected to be related to or affectthe depended variable in the study.
Measure the average income of households
Education Sex Race Household head
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Conducting a survey of 200
500
liberal
artmajo
r
500 liberal art major
100enginee
ringmaj
o
100 engineering major
200busi
nessmaj
200 business major
125li
beral
artma
jo
r
125 liberal art major
25eng
ineeri
ngma
jo
r
25 engineering major
50
busin
essma
jo
50 business major
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If we want to investigate some questions in eachmajor separately
Number LA Engin Business Total
Stud. 500 100 200 800
P.W 0.625 0.125 0.25 1
Size
Sample
100 50 50 200
Samplemeangrade
2.5 3.3 2.7 2.65
100li
beral
artma
jo
r
100 liberal art major
50eng
ineeri
ngma
jo
r
50 engineering major
50
busin
essma
jo
50 business major
Weighting factor
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Describe thepopulation
The mean would be = 0.625 (2.5) + 0.125 (3.3) + 0.25 (2.7)= 2.65
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Cluster SamplesThe list of elements does not exist
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Cluster sample
Is a probability sample in which the sampling frameinitially consist of cluster of element
It is groups or clusters of elements are identified and listedas sampling unit
The sample is drown from the list of sampling units
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POPULATION
CLUMP
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POPULATION
Primary samplingUnit
POPULATION
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POPULATION
= Randomly selected PRIMARY SAMPLING UNITS.
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Cluster samplingSome populations are spread out (over a state or country).
Elements occur in clumps (towns, districts)Primary samplingunits.
Elements are hard to reach and identify.
You cannot assume that any one clump is better or worse thananother clump.
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Opinion Poll of 1000 people in a city
Obt
ainingama
pofth
e
Obtaining a map of thecity
Identi
fyingandli
s
Identifying and listing allblocks
Sm
allnum
berof
b
Small number of blocks are sampled at random orsystematically
Sele
ctthe
d
Select the dwellingunits
Contac
t
Conta
ct
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Opinion Poll of 1000 people in a city
1
2
3
The probability of one household being selected is :25/500 x 1000/4000 = 1/80
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Cluster sampling
Reduces fieldwork cost
Reduces travel andadministrative costs
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Errors
Errors occur at each stage of the cluster sample
The random errors at each levels must be added together to arrive at
the total sampling error for a cluster sample
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What to chose?
40 individuals from 25 blocks
25 individuals from 40 blocks
Homogenous population
States regions
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Nonprobability Samples
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NonprobabilitySamples
Is a sample for whicheach element in the total
population has aunknown probability ofbeing selected
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Third level Fourth level
Fifth level
P
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NonprobabilitySamples
Pur
posiv
esam
ple
Purposive sample
Conve
nienc
esam
pl
Convenience sample
Qu
otasa
mple
Quota sample
Snow
ballsa
m
Snowball sample
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NonprobabilitySamples
To expensive
Unusual cases
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Purposive sample
Researcher exercisesconsiderable discretion
over what observationto study
Study a diverse andusually limited numberof observations
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Convenience Sample
Elements are includedbecause they are
convenient or easy toreachI havesomequestions
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Quota sample
Elements are sampledin proportion to their
representation in thepopulation
Stratified vs Quota ?
Elements in the quota
sample are not chosenin a probabilisticmanner
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Quota sample
550 women
450 men
Select whomever theypleased until the
quota were reached
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Snowball sample
The respondents areused to identify other
persons who mightqualify for inclusion inthe sample.
The elements are askedto supply appropriatenames for furtherinterviewing
We interview untilenough persons are
interviewed to satisf
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Snowball sample
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Sample Statistics
Parameter: any characteristic of a population that is trueknown on the basis of a census (e.g., % of males orfemales; % of college students in a population).
Estimate: any characteristic of a sample that is estimatedestimated on the basis of samples (e.g., % of males or
females; % of college students in a sample)
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Sampling error
An estimate of precision; estimates how close sampleestimates are to a true population value for a characteristic.
Occurs as a result of selecting a sample rather thansurveying an entire population
A measure of
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S t a n d a r d E r r o r
A measure ofsampling error.
Sample size As sample size
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SE is an inverse function of sample size
Sample size
Standard
pincreases, SEdecreasesthesample is more
precise.
So, we want to usethe smallest SE wecan greatest
precision!
When in doubtincrease sample size.
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How large a sample?
Third level Fourth level
Fifth level
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?
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