POL SOC 360 Sampling Generalizability

1. POL / SOC 360-01
Spring 2015

4.  Definition of Population
 Population should be:
 Carefully and Fully Defined
 Relevant to Research Question
 Remember McDonald and Popkin study?
 How did they define their population?

5.  Definition of Sample
 Importance of Sample Data
 Quality of Sample Based on:
 Overall Sample Size
 How members chosen to be part of sample

6.  Advantages of Sample
 Time
 Money
 Disadvantages of Sample
 Less accurate
 Subject to error
 Decision made on practical grounds

7.  Population Parameter
 Characteristics about population quantified as a
number
▪ Examples: Proportion, Mean/Average, etc.
 Estimator
 Numerically estimates the value of population
characteristic, or population parameter

8.  Sample Statistic
 An estimator of a population parameter derived from a
population sample
 Element
 Also called a unit of analysis
 A single occurrence, realization, or instance of the
objects or entities being studied
▪ Examples: Individuals, States, Cities, Countries,
Speeches, Wars

9.  Stratum
 Population subdivided into groups of similar
elements before a sample is drawn
 Subgroup of a population sharing characteristics
 Examples:
 MSU students stratified by class, major, or GPA
 Latin Graduation Honors

12.  Sampling Frame
 Particular population from which sample is drawn
 Closer sampling frame is to population of interest or
theoretical population, the better off you are
 Example:The Literary Digest Poll?

13.  If sampling frame is incomplete or inappropriate, then
sample bias will occur
 Sample will be unrepresentative of the population,
and inaccurate conclusions may result
 Sample bias caused by a biased selection of elements,
even if frame is complete and accurate
 Sampling Unit
 Entity listed in a sampling frame

14.  Probability Sample
 Sample for which each element in the total
population has a known probability of being
included in sample
 Nonprobability Sample
 Sample in which each element in the total
population has an unknown probability of being
selected

16.  Each element and combination of elements has an
equal chance of being selected
 What has to happen for this to occur?
 Short Class Activity on Random Numbers

17.  Attempt to make draft process fairer
 How did the lottery process work?
 Selective Service (SS) estimated that anyone
with number higher than 200 would not be
called
 Found negative correlation between day of
birth and lottery number

18.  Random Numbers Generator

19.  Elements selected from list at predetermined
intervals (e.g. every Kth element)
 K = Sampling Interval or “skip” between elements
 Computed as Population Size (N) / Sample Size (n)
 Useful when dealing with long list of population
elements (e.g. all SC justices)
 Often used in product testing

20.  Probability sample where elements sharing
one or more characteristics are grouped
 Two MainTypes:
 Proportionate Sample
 Disproportionate Sample

21.  Stratified sample were each stratum
represented in proportion to its size in
population
 Example: Congress of the Future
 Sampling Fraction

22.  Stratified sample where each stratum is NOT
represented in proportion to size in population
 Issue ofWeighting

23.  Probability sample in which sampling frame
initially consists of clusters of elements
 Groups / clusters of elements are identified and
listed as sampling units
 Within each sampling unit, certain elements are
identified and sampled
 Example: Public Opinion Polling

24.  Advantages:
 Allows researchers to get around problem of
acquiring list of elements in target population
 Can reduce fieldwork costs
 Disadvantage:
 Greater level of imprecision

26.  Goal: To study a diverse and usually limited
number of observations
 Researcher exercises considerable discretion
 Example: Fenno and Home Style

27.  Elements are included because they are
convenient or easy for a researcher to study
 Used for exploratory research or when target
population is impossible to define / locate

28.  Sample in which elements are sampled in
proportion to their representation in
population
 Similar to proportionate stratified sampling,
but elements are quota sample are NOT
chosen in reasoned or probabilistic manner

30.  Initial respondents used to identify others
who might qualify for inclusion in sample
 Useful when trying to study members in
elusive population:
 Draft Dodgers
 Political Protestors
 Drug Users