STAT 100 Lecture Notes - Lecture 11: Stratified Sampling, Sampling Frame, Statistical Inference

• School: University of Maryland
• Department: Statistics and Probability
• Course: STAT 100
• Professor: Susan Mazzulo

Document Summary

Researchers often want to answer questions about some large group of individuals population. Often the researchers cannot measure all individuals in the population, so they measure a subset of individuals that is chosen to represent the entire population sample. A sample design describes exactly how to choose a sample from the population. The research then use statically techniques called statistical inference to make conclusions about the population based on the sample. Selects a sample from the population of all individuals about which we desire information. Individuals in sample are representative of the population. Minimize cost of obtaining the sample (money time and personnel) A sample would be biased if it is not representative of the population. Convenience sample: select individuals that are mostly readily accessible, ma(cid:374)y people are(cid:374)"t sa(cid:373)pled and many answers are done, pretty bad, convienent slow mice- the one that they took.