Sample Surveys

Report
Sample Surveys
Ch. 12
The Big Ideas
1. Examine a Part of the Whole
2. Randomize
3. It’s the Sample Size
Examine a Part of the Whole
Population -- the entire group of individuals that
we want information about
Sample -- a part of the population that we
actually examine in order to gather information
Sampling vs. Census
Sampling
• Studies a part to gain
information about the
whole
• Powerful (when done
correctly)
Census
• Attempts to gather
information from every
member of the population
• Difficult
• Time consuming
• Expensive
• (Sometimes) Impossible
Methods of Sampling
Good
• Simple Random (SRS)
• Stratified Random
• Cluster
• Multistage
• Systematic
Bad
• Voluntary Response
• Convenience
Bad Sampling Methods
Voluntary Response Sample
– A large group is invited to respond and all who
respond are counted
– Internet polls, radio call in polls, etc.
– Skewed toward extreme opinions
Convenience Sample
– Only include individuals who are convenient to
sample
– Lazy
Good Sampling Methods
Simple Random Samples (SRS)
– Every individual has equal chance of being
selected, every subgroup (of the desired sample
size) has equal chance of being selected
Good Sampling Methods (cont.)
Stratified Random Sample
– Divide the population into groups (strata) that are
similar in some way
– Choose a SRS in each stratum
– Combine the SRSs from each strata to form the full
sample
Good Sampling Methods (cont.)
Cluster Sample
– Divide population into groups (aka clusters)
– Randomly select clusters
– All individuals in the chosen clusters are selected
for the sample
Good Sampling Methods (cont.)
Systematic Sampling
– Start the sample with a random selection
– Select every nth person until you reach your
sample size
Good Sampling Methods (cont.)
Multistage Sampling
– A combination of different sampling methods
Bias
• The result of sampling methods that over or
under emphasize some characteristic of the
population
Bias
• It is very difficult to recover good data once
bias is introduced
• Spend the time/effort/money to ensure an
unbiased
Randomize
• Randomizing our selection helps to ensure
that on average the sample looks like the
population
Types of Bias
Voluntary Response Bias
– Survey participants self-select to be included in
the survey
Nonresponse Bias
– Not everyone chosen for the survey responds
Response Bias
– Anything in the design that influences the
responses

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