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Random Sampling
Each thing has the same chance of being selected.
Simple Random Sampling
Has a requirement + not all sets have the same chance of being selected.
Stratified Sample
Ex: Freshman, Sophomore, Junior, Senior, Grad
→ sample from each group.
Cluster Sampling
West Davis, South Davis, East Davis, North Davis, Central Davis.
→ Randomly select clusters + All info from each cluster.
Systematic Sample
Every “nth “ piece of data
Convenient Sampling
Sample being drawn from part of the population that is close to hand
Nominal
Categorize
→ Ex: eye color
Ordinal
Categories that can be put in order
→ Ex: Letter Grades
Interval
Categories that can be put in order and subtract values
→ Ex: Temperature *0 does not mean none
Ratio
Categories that can be put in order and can subtract values, and determine if its a multiple of each other.
→ Ex: Exam Scores *0 means none