Designing a Statistically Sound Sampling Plan
Designing a Statistically Sound Sampling Plan
Presented by: Steven Walfish President, Statistical Outsourcing Services steven@
Purpose and Objectives
z Objective:
z Define different types of sampling including random, stratified and composite.
z Create and justify your sampling plan.
z Account for sampling and measurement error.
z Determine the relationship between sample size, statistical power and statistical precision
z Sampling plans for attribute data.
Sampling Plans
z Decisions are often based on our analysis of a sample.
z How we conduct a sample is very important.
z Minimize bias z Representative sample z Sufficient size.
Sampling Plans
z Simple Random Sample
z Each sampling unit has an equal probability of being sampled with each selection.
z Can perform simple random sampling if:
z Enumerate every unit of the population
z Randomly select n of the numbers and the sample consists of the units with those IDs
z One way to do this is to use a random number table or random number generator
Sampling Plans
z Stratified Random Sampling:
z Population strata which may have a different distribution of variable.
z Strata must be known, non-overlapping and together they comprise the entire population.
z Examples: z Measuring Heights: Stratify on Gender
Strata are Male, Female
z Clinical study: stratify on stage of cancer z Measuring Income: Stratify on education or years of
experience
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