PO217 Lecture Notes - Lecture 6: Statistical Inference, Sampling Distribution
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Problem: the populations we wish to study are almost always so large that we are unable to gather information from every case. Solution: we choose a sample- a carefully chosen subset of the population and use information gathered from the cases in the sample to generalize to the population. In estimation procedures statistics calculated from random samples are used to estimated the value of population parameters. You want to know what % of students at a large university work during the semester. Draw a sample of 500 from a list of all students at the university (n=20,000) Assume the list is available from the registrar. After questioning each of these 500 student (from the 20,000 students), you find that 368 (74%) work during the semester. Based on the example above, identify each the following. Parameter: how many of the 20,000 students work. Definition: the theoretical, probabilistic distribution of a statistic for all possible samples of a given size (n)
