1. §2.3: Sampling Methods

2. Sampling
data collection that involves the selection of an unbiased or random subset of individual observations

3. Sampling Process
Determine the population
Select a sampling method
Determine the sample size
Sample and collect data

4. Sampling Methods Random Sampling
sampling in which selections are made without prejudice or bias
Non-random Sampling
sampling in which selections are made with prejudice and/or bias

5. Simple Random Sampling
Every member of the population has equal probability of being selected
Putting names in a hat and blindly choosing
Sometimes just referred to as random sampling

6. Systematic Random Sampling
requires a list of the population
this list should not be sorted or even partially sorted to any criteria
pick every nth item/person on the list
n should be between 1 and pop/sampsize

7. Stratified Sampling
stratified related to the word “stratum” meaning layer
break up the population into categories (males & females, age strata)
proportionally sample each strata relative to its representation in the population

8. Cluster Sampling sometimes called block sampling
population should be divided into groups that are heterogeneous and representative of the population
a sufficient number of groups are selected to meet the sample size requirement

9. Multi-Stage Sampling
basically two part sampling using sampling methods we already know
Cluster sampling
Simple random sampling
This is why cluster sampling must have
groups that are already representative of
the population

10. Snowball Sampling start out with a partial sample of the population
ask all members of that sample to suggest or invite others to be a part of the sample group
continue until you reach your sample size
useful for groups of people who aren’t accounted for easily (eg. homeless individuals)

11. Homework
Pg 99 #1, 3