• Briefly define: (a) Parameter- is the population in which we are interested in. This could be how many students are taking business courses, accounting courses, or sociology courses. (b) “An estimator is a statistic derived from a sample to infer the value of a population parameter” (Doane & Seward, 2007). (c) Sampling error- is the difference between an estimate and the population parameter. Sampling error occurs because the samples will have different variables dependent upon changes in the population being sampled. (d) Sampling distribution- is probability distribution of the possible values that may come from random samples. (e) Point estimate- is the sample mean that is calculated from a random sample. This estimate is necessary to highlight the unknown about the true value. (f) Interval estimate- is the interval of several probable values from a random sample. This differs from point estimate in that it has several different values instead of a single variable. (g)
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This note was uploaded on 06/25/2011 for the course RES 341 taught by Professor Hermis during the Spring '10 term at University of Phoenix.