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Statistics
The theory of decision making
Data
Observations
Population
All individuals of interest
Parameter
Numerical characteristic of a population
Sample
Subset of the population
A statistic
Numerical characteristic of a sample
Two types of data
Quantitative (numerical) and Qualitative (categorical)
Discrete (Quantitative data)
finite or countably infinite # of possibilities
Continuous (Quantitative data)
Uncountably infinite # of possibilities
Nominal (level of measurement)
Qualitative, no math can be done
Ordinal (level of measurement)
Qualitative, can be ranked but differences meaningless
Interval (level of measurement)
Quantitative, can be ranked, differences meaningful, 0 is not inherent
Ratio (level of measurement)
Quantitative , can be ranked, differences meaningful, 0 is inherent
Simple Random Sample (SRS)
Every sample of the same size n has the same chance of selection
Stratified Sample
Break population into homogeneous groups and take a SRS from each group proportionally
Systematic Sample
Take every kth person
Cluster sample
Take entire subgroups
Mean and s
Any points outside mean+-3s
5# Summary
Min, max, Q1, M, Q3
Density Histogram
height=fraction ÷bin width