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

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

(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

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.

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

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.

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: 2401/21909 = 11%, .11(100) = 11 3) Obtain Simple Random sample within each strata

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

Obtaining a Systematic Sample k 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

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

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