1. Statistics – Chapter 1 Data Collection
1.3 Other Effective Sampling Methods
Objectives:
Obtain a stratified sample
Obtain a systematic sample
-Obtain a cluster sample

2. Sampling Techniques Simple Random Sample Stratified Sample
Goal: To obtain individuals for a study in such a way that accurate information can be obtained.
The 4 Basic Sampling Techniques are:
Simple Random Sample
Stratified Sample
Systematic Sample
Cluster Sample

3. (Money, time, and resources)
Stratified Sample
One goal of sampling is to obtain as much information as possible with the least amount of cost
A is obtained by separating the population into non-overlapping groups called strata and obtaining a simple random sample from each stratum.
Members of each strata are homogenous in some way (homogenous = the same)
(Money, time, and resources)
Stratified Sample

4. Advantages of Stratified Samples
Allows for surveying less people in a population while obtaining the same or more information
Guarantees each stratum is represented, not one-sided
Why stratified and not simple random?
The researcher is able to determine characteristics within each stratum. Analysis can be done on each subgroup to see if differences (or similarities) exist.

5. How to Obtain a Stratified Sample
Determine your strata to be surveyed
Weight each strata by population size
Conduct a simple random sample within each strata
Random Number Generator or Table
Going to need a frame to complete SRS

6. Stratified Sample Example
The president at DePaul University wants to conduct a survey to determine the community’s opinion on campus safety, and divides the community into 3 groups: resident students, non-resident students (commuters), and staff.
There are 6,204 resident students, 13,304 non-resident students, and 2,401 staff for a total of 21,909 in the population
The president wants to obtain a sample of size 100.

7. Stratified Sample Example
1) Determine the strata
Resident students, Commuter students, staff
2) Weight each according to population
Resident students: 6204/21909 = 28%, .28(100) = 28
Commuters: 13,304/21909 = 61%, .61(100) = 61
Staff: /21909 = 11%, .11(100) = 11
3) Obtain Simple Random sample within each strata

8. Systematic Sample Systematic Sample k k
A is obtained by selecting every th individual from the population.
The 1st individual selected is a random number from 1 to .
No frame required here, so its useful when no list is available. k k

9. Obtaining a Systematic Samplek
Select a number
Randomly select a number between 1 and
Select that person, then every th person after
How do we decide k?
Small enough that it reaches your sample size
Large enough to include representative sample of all data
Estimate of population size necessary to determine appropriate k.
If we know N (population size), then we divide N/n and round down to get k. k k

10. Cluster Sample Cluster Sampling
is selecting all individuals within a randomly selected collection of individuals
Example: Surveying households by city blocks
Number all the city blocks
Pick random blocks
Survey all houses on the blocks
Homogenous vs. Heterogeneous clusters
Homogenous = similar individuals, fewer clusters
Heterogeneous = dissimilar individuals, more clusters

13. Other Samples
Convenience Sampling = sample in which the individuals are easily obtained
Self selected , voluntary response
Multistage Sampling – a combination of the previous sampling techniques