Population of interest
Entire collection of individuals
Sample
Individuals selected for study out of population
Parameter
Numerical summary of population
Statistic
Numerical summary of sample
Respondents
Individuals who answer a survey
What are categorical variables also known as?
Qualitative variables
Categorical variables
Has categories, groups, or levels
Two types of categorical variables
Nominal –> no order
Ordinal –> has order or ranking
What variable do you use proportion for?
Categorical variable
Numerical variables
Measures quantity or amount
What are numerical variables also known as?
Quantitative variables
Two types of numerical variables
Discrete –> whole numbers
Continuous –> include decimals
Random sampling
Randomly selecting people from population
Random allocation
Randomly assign individuals into different treatment groups
Population inference
Generalized to entire population
Casual inference
Conclusion about cause-and-effect relationship
(different outcome caused by different treatments)
When do you make casual inference?
When have random allocation
When do you make a population inference?
When have random sampling
Simple random sampling (SRS)
Each individual has equal chance of getting chosen
Stratified random sampling
Divide population into groups with similar characteristics (strata) then take SRS on each strata
Systematic Random Sampling
Start from randomly selected person then sample every kth person
Cluster random sampling
Split population into small groups and perform census
Selection bias
Part of population not sampled or has little representation
Respinse bias
Survey design influences persons response
