12 – Sampling

Why Should I Care?

A bad sample will kill your scientific power. That’s all there is to it.

Definitions

Population                    A set of observable objects, which could be individuals, groups, documents,                                                 organizations, etc. that you are interested in studying.

Sample                          Groups of objects, taken from a population, that are studied on behalf of the                                               population. Will be used to generalize about the population.

Caveat                          a warning or proviso of specific stipulations, conditions, or limitations.                                                        Especially important in the methodology section, to provide transparency, and                                                discuss the strength of the findings. Acknowledges problems in method. (WIKI)

 

Deciding to Sample

1st Question: can you avoid sampling?

                                                                        If n=N, best possible situation

Is it possible? Is it feasible?

Do you have enough time, resources, tools to collect data for the whole population?

A Good Sample

Generalization:                          To be able to use a sample finding, and assume it is accurate upon the                                                         population.

Causality:                                  Finding the variable(s) responsible for a change in the dependent                                                                variable.

SOUP EXAMPLE

Population:                                2 litres of vegetable soup in a pot

Sample:                                     1 spoonful

Random Selection?                     No, the bottom soup may never be tasted

Representative?                          Maybe, if you stir before you sample.

Type?                                        Non-random quota

The Power of a Good, Small Sample

EXAMPLE: 1995 QUEBEC REFERENDUM

See p. 73 – Results from polls are shown before the results from the actual referendum.

What was the population studied?                        Quebec adult voting population. ~ 5 million

What was the sample size?                                              ~ 1000

How accurate are the survey results?                                Very

How old were you when this happened?                           17

 

Types of Samples

Who should be in the sample?

The type of sample is the key to producing a research finding that is robust and credible. This applies to all disciplines and all research methods. P. 76-90

1. Random Sample Generalizable

1. Simple Random Samplemath rule Xth

1. Stratified Random Samplerespect the population percentage of demographics

1. Random Assignment is not Random Samplinggoing to caf is not random

1. Non-Random SampleNOT GENERALIZABLE
2. Accidental Samplefind documents or objects          
3. Convenience Samplegoing to a location where there are people
4. Purposive Sampleplace where you know you will find XYZ people
5. Quota Samplerespect the population percentage of demographics
6. Snowball Sampleone case leads to more, and more, and more…

Size of the Sample

How big the sample?                                          Big enough for most sorts of phenomena to be recorded

Accuracy is not generalization.                             This has to do with the margin of error. See QM.

Is 10 big enough of a sample to be accurate?         Depends on the size of the population.