How and Why Do Samples Work?
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a small collection of units taken from a larger collection
Sample

a larger collection of units from which a sample is taken
Population

a sample drawn in which a random process is used to select units from a population
there are best to get an accurate representation of the population
but are difficult to conduct
Random sample

a nonrandom sample in which you use a nonsystematic selection method that often produces samples very unlike the population
 Four Types of NonRandom Samples
 Convenience sampling(Accidental or Haphazard)

nonrandom sample in which you use any means to fill preset categories that are characteristics of the population
 Four Types of NonRandom Samples
 Quota Sample

a nonrandom sample in which you use many diverse means to select units that fit a very specific characteristics
 Four Types of NonRandom Samples
 Purposive(Judgmental) sampling

a nonrandom sample in which selection is based on connections in a preexisiting network
 Four Types of NonRandom Samples
 Snowball(network) sampling

a specific list of sampling elements in the target population
Sampling frame

any characteristic of the entire population that you estimate from a sample
population parameter

the ration of the sample size to the size of the target population
sampling ratio

Why use a Random Sample?
Random samples are most likely to produce a sample that truly represents the population
they are purely mathematical or mechanical
allow calculation of probability of outcomes with great precision

sample elements selected from the frame based on a mathematically random selection procedure
simple random samples