SOCPSY 2K03 Lecture Notes - Lecture 4: Quota Sampling, Quasi, Multistage Sampling
31 Jan 2020
School
Department
Course
Professor
Sampling - process of selecting observations
Population - any entire collection of people, groups, organizations, or things from which
we may collect data. It is the entire group we are interested in, which we wish to describe
or draw conclusions about
Sample - a group of units selected from a larger group
Element - unit of which a population is comprised and which is selected in a sample. Unit
about which inferences are made
2 major types of sampling
Non probability sampling
Reliance on available subjects
○
Purposive sampling
○
Quota sampling
○
Selecting informants
○
1.
Probability sampling
Key to generalizing from a sample to a larger population = prob sampling
○
Involves random sampling
○
Random: any outcome has the exact same chance of occurring as any other
outcome
○
Random sampling: every unit of observation in a population has same chance
of being selected into a sample
Helps produce samples that are representative of the wider population
that they are drawn from
§
While random sampling does not guarantee a representative sample, it
does allow us to measure the degree of error in our estimates
§
○
2.
Theory of logic and probability sampling
Logic of Sampling
Thursday, January 30, 2020
3:31 PM
Theory of logic and probability sampling
Representativeness and probability of selection
Biased samples - do not allow us to make accurate inferences about the population they
are drawn from
How to reduce bias
All members of given populations should stand an equal chance of being selected
for a particular sample. The term for this is equal probability of selection method or
EPSEM
-
Bigger samples are better than smaller samples, although there is a diminishing
return to larger samples
-
Populations and sampling frames
Difficult to get info about whole population
-
To solve problem, sampling frame is drawn. It’s a list of elements composing a
population from which a sample is drawn. If the sample is to be representative of
the population, its essential that the sampling frame include all members of
population
E.g., Mac directory of all undergrad students
○
CABWSH survey (population = Canadian workers)
Quasi sampling frame : national list of phone numbers
Why quasi? Not comprehensive list
□
§
○
-
Types of sampling designs
Simple random
1.
Systematic
2.
Stratified
3.
Document Summary
Population - any entire collection of people, groups, organizations, or things from which we may collect data. It is the entire group we are interested in, which we wish to describe or draw conclusions about. Sample - a group of units selected from a larger group. Element - unit of which a population is comprised and which is selected in a sample. Key to generalizing from a sample to a larger population = prob sampling. Random: any outcome has the exact same chance of occurring as any other outcome. Random sampling: every unit of observation in a population has same chance of being selected into a sample. Helps produce samples that are representative of the wider population that they are drawn from. While random sampling does not guarantee a representative sample, it does allow us to measure the degree of error in our estimates.
