STATS VOCAB
*Variable-characteristic attribute that varies in value and example
*Data- values the variables assume
*Data set-collection of values
*Data value-each value in set
*Population-complete set of all subjects being studied,
*Sample-subgroup of population
*Qualitative- data in the form of words
*Quantitative-data in the form of numbers
*Internal stats- predict, generalizing information
*Descriptive Stats- collecting, information that is summarizing data
RANDOM SAMPLING TECHNIQUES
Simple Random Sample: Everyone has equal chance a being sampled
Stratified Sample: Population is grouped by characteristic and a sample is randomly
selected from every group. (Ex. Grouping a class by favorite color, and choosing a
representative of each group to be a sample)
Cluster Sample: Population is divided & each data valve is given a serial number,
number each divided group, find number in table between 1- (# of groups) and use all
data values in random chosen group as samples.
*Variable-characteristic attribute that varies in value and example
*Data- values the variables assume
*Data set-collection of values
*Data value-each value in set
*Population-complete set of all subjects being studied,
*Sample-subgroup of population
*Qualitative- data in the form of words
*Quantitative-data in the form of numbers
*Internal stats- predict, generalizing information
*Descriptive Stats- collecting, information that is summarizing data
RANDOM SAMPLING TECHNIQUES
Simple Random Sample: Everyone has equal chance a being sampled
Stratified Sample: Population is grouped by characteristic and a sample is randomly
selected from every group. (Ex. Grouping a class by favorite color, and choosing a
representative of each group to be a sample)
Cluster Sample: Population is divided & each data valve is given a serial number,
number each divided group, find number in table between 1- (# of groups) and use all
data values in random chosen group as samples.
