Types of Sampling Simple Random Cluster Stratified Systematic

Types of Sampling Simple Random Cluster Stratified Systematic (every kth element is sampled)

Assumptions Members of the Population can be numbered from 1 to N where N is the population size You have a mechanism for randomly picking n numbers (usually without replacement) from the collection of numbers 1, 2, 3, …, N If number k is selected, the population element with that number is in the sample

Simple Random Sample Population above right In a Simple Random Sample each population member is equally likely to be selected Click to sample 1 6 2 12 3 4 5 17 18 8 13 14 10 9 16 7 15 20 19 21 11

Cluster Sampling The Population (right) can be divided into strata A stratum consists of population elements that are similar in some way All of one or more strata are randomly selected and used in the sample—see next slide 1 13 2 14 12 4 3 17 5 8 6 7 9 11 10 15 24 16 22 21 19 23 20 18

Population Above—Click to take a Cluster Sample 1 2 4 3 6 12 5 8 7 10 9 11 15 24 13 14 17 16 22 19 23 20 21 18

Stratified Sampling The Population (right) can be divided into strata A stratum consists of population elements that are similar in some way A random sample from each stratum is randomly selected and used in the sample—see next slide 1 13 2 14 12 4 3 17 5 8 6 7 9 11 10 15 24 16 22 21 19 23 20 18

Population Above—Click to take a Stratified Sample 1 2 4 3 6 12 5 8 7 10 9 11 15 24 13 14 17 16 22 19 23 20 21 18

Systematic (every kth) A starting number is randomly chosen The population element corresponding to the starting number and every kth population element after that are selected for the sample ‘Circular’ counting is used

Every 7 th Element Sample Population above right Click once to get a random starting element Click again to get every 7 th element after that 1 6 2 12 3 4 5 17 18 8 13 14 10 9 16 7 15 20 19 21 11