STAT 100 Lecture Notes - Lecture 7: Royal Institute Of Technology, Sampling Frame, Sampling Bias

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

Document Summary

Researchers often want to answer questions about some large groups of individuals. (this group is called the population. ) Often the researchers cannot measure (or survey) all individuals in the population, so they measure a subset of individuals that is chosen to represent the entire population. (this subset is called a sample. ) A sample design describes exactly how to choose a sample from the population. The researchers then use statistical techniques (called statistical inference) to make conclusions about the population based on the sample. Sample survey: selects a sample from the population of all individuals about which we desire information. Individuals in sample are representative of the population (provide accurate information about the population) Minimize cost of obtaining the sample (money, time, personnel, etc. ) A sample is biased if it is not representative of the population. Biased samples tend to systematically overrepresent certain segments of the population and systematically under-represent other segments.