STAT141 Chapter Notes - Chapter 11-13: Royal Institute Of Technology, Random Assignment
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Census: special sample that includes everyone and samples the entire population. Statistic: summary that is found from data in a sample. Parameters: describes a characteristic of the population; often found with population inference. Types of conclusions: population inference: generalizing results from a sample to an. => require random sampling; non-random sampling leads to entire population. Biased results: casual (cause & effect) inference: difference in responses caused by the difference in treatments when comparing the results from two treatment groups. => require random allocation ( ) and random assignment; or lurking variables could create change. Random sampling methods: simple random samples (srs) Randomly selecting samples; every individual has an equal chance of being selected: stratified random sampling. Population divided into homogeneous groups (strata) for srs testing; results combined: systematic random samples. Systematic selection where every kth previously randomly selected individual is sampled: cluster random sampling. Population divided into identical groups; randomly select group/s to perform census test: multi-stage sampling.
