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Key terms
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Simple Random Sample
Every possible sample in the population has an equal chance of being selected
Stratified Sample
Divide population into groups, chose random groups
Cluster Sample
Divide population into areas (clusters), then randomly select
Systematic Sample
Sample every X instance
Multistage Sample
Combining methods
Bad Sampling Frame
Hard to list everyone
Under coverage
Missing or underrepresented groups
Non-response Bias
Hard to contact
Response Bias
Untruthful
Wording and Order
Elect a certain response
Completely Randomized Design
Random people to random treatments
Randomized Block Design
Divide into subgroups called blocks
Matched Pair Design
Like randomized block design but when there is only two treatment groups
Type 1 Error
We reject the null hypothesis when it is true
Type 2 Error
We accept the null hypothesis when it is false