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simple random sampling
equal chance from population

systemic sampling
 order population, then every otherĀ
 e.g. alphabetical then every 3rd person

stratified sampling
 divided into stratas, randomly selected fr each
 smaller scale
 a farmer wishes to work out the average milk yield of each cow type in his herd which consists of Ayrshire, Friesian, Galloway and Jersey cows. He could divide up his herd into the four subgroups and take samples from these

cluster sampling
 naturally occurring geographic other boundaries
 random selected within
 larger scale
 Department of Agriculture wishes to investigate the use of pesticides by farmers in England. A cluster sample could be taken by identifying the different counties in England as clusters. A sample of these counties (clusters) would then be chosen at random, so all farmers in those counties selected would be included in the sample. I

quantitative: discrete vs continuous
 discrete: counting
 continuous: measuring

nominal scale
 mutually exclusive (only one category)
 no particular order
 e.g. marriage status canadians single, married, divorced, widowed

ordinal scale
 objects in order
 e.g. students according y ear rank

interval scale
 order w/ equal distance
 negative values allowed
 e.g. temperatures celsius

ratio scale
 absolute zero point
 e.g. weight, mass

