1.5 Sampling Techniques, Design of Experiments/Observations. How to Develop a Random Sample Theory

Observation

(1) measures specific traits, does not modify subjects

Experiment

(1) apply treatment, measure effects, modify subjects

Examples of Observations

(1) polling

Examples of Experiments

(1) drug treatment

Definition of Random Sample

(1) each member of population has equal chance of being selected in the sample

Definition of Simple Random Sample

(1) Each possible sample of size n has equal chance

(2) Every individual in the group of size n has an equal chance of being chosen

(applies to choosing individuals within a population)

4 Common Sampling Techniques

(1) Convenience Sampling

(2) Systematic Sampling

(3) Stratified Sampling

(4) Cluster Sampling

Convenience Sampling

(1) use the results that are easy to get

(2) not random

Example of Convenience Sampling

(1) asking random bystanders on the street

Systematic Sampling

(1) order population, start at random spot, select every k^th member

Stratified Sampling

(1) break population into characteristic subgroups, sample each subgroup

(may be in conjunction with systematic sampling)

Cluster Sampling

(1) break population into non-characteristic clusters, select a number of every k^th cluster, collect data from the entire cluster

Non-Sampling Error

(1) just getting the wrong math

Sampling Error

(1) difference in characteristics between sample and population