notes/education/statistics/Sampling.md

(Ch 19, stat 1040)

Term	Definition
Qualitative	A descriptive value (red, blue, high, low)
Quantitative	A numerical value (7, 8, 9)
Population	The entire set of existing units that investigators wish to study
Sample	A portion or subset of the population
Parameter	A number that describes a characteristic of a population (10% of US senators voted for something)
Statistic	A number that describes a sample characteristic (71% of Americans feel that ...)

A global consumer survey reported that 6% of US taxpayers used or owned cryptocurrency in 2020. The US government is interested in knowing if this percentage has increased. The University of Chicago surveys 1,004 taxpayers and finds that 13% have used or owned crypto in the past year (2021)

In the above example:

• The population was US taxpayers
• The parameter was 6%
• The sample was 1004 taxpayers
• The statistic was 13%

An ideal sample will represent the whole population.

Sampling

Sample Type	Description
Simple random	Advantages: - Procedure is impartial - Law of Averages Disadvantages - Not always possible - Can be very expensive
Quota Sampling	Attempts to get certain proportions based on key characteristics. Quota sampling doesn't guarantee that the selection is an accurate representation.
Cluster Sampling	Divide population into subgroups, randomly select a subgroup, and sample all of the subjects in that group
Convenience	Sampling done near to the researcher because it's easier.

Simple Random Samples

Bias

Bias Type	Description
Selection	When the procedure that selects the sample is biased
Non-Response	Those that don't respond to a survey may have different characteristics than those that do respond
Response	When the question is worded in a leading way to elicit a certain response.
Volunteer response	Self selecting, individuals volunteer to answer
Measurement	Interviewing method influences the response, uses loaded words or ambiguities.
(Ch 20, stat 1040)