Sampling variability- the differences between each sample that we draw at random "sample-to-sample differences* Sampling frame - A list of individuals from whom the sample is drawn individuals who may be in the population of interest but who are not in the sampling frame cannot be included in any sample. This is what we measure all other sampling methods against and what we hope every sampling method is achieving. Simple Random Sample (SRS)- each combination of people has an equal chance of being selected. Statistic- any summary found from the data Parameter- The numbers in the model that have to be chosen to explicitly determine the value of the model. The best defense against bias is randomization.Ĭensus-a sample that consists of the entire population. Randomization- Each individual is given a fair, random chance of selection. Sample survey- a study that asks questions of a sample drawn from some population in the hope of learning something about the entire population.īiased- a sample that does not represent the population in some way, it overlooks an important group. Sample- A smaller group of individuals selected from a population. Population- A large group of individuals usually impractical to measure.
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