Population and Samples
Population: whole collection of people that information is sought out from
Census: collection of data from every subject matter in population
Sample: specific bit of population where data is collected from
Whether certain data is seen as population or sample depends on who is viewing it.
The definition of population depends on what you’re trying to study.
Parameter
Statistic
Inference
The process of drawing conclusions based on a sample.
Bias
Voluntary Bias
Convenience Sampling
Systematic Sample
Step 1: Randomly select starting point
Step 2: Select every kth item after
Simple Random Sample
When everyone has an equal chance of being chosen.
Variability
Studies should have low bias and low variability
Random sampling + Larger samples = fair results
Explaining Bias
Step 1: How will sampled individuals differ from the rest of the population
Step 2: How this results in overestimate or underestimate
Observational Studies
Retrospective: examines existing data or asks about past behaviors
Prospective: follows individuals to gain further data
Sampling Frame
List of individuals that sample is drawn from
Non Sampling Errors
These can also be in a census. Increasing sample size won’t reduce error.
Non Response Bias
When some individuals can’t be contacted or when people lie, don’t respond, or partially respond.
Response Bias
When there are problems with the data gathering instrument
Question Wording Bias
The wording of questions can influence answers.
Stratified Random Sampling
Step 1: Divide into distinct groups (stratas)- homogeneous grouping
Step 2: Use a method of random number selection and pick from each stratum to form the complete sample
Cluster Sampling