STAT 213 Lecture Notes - Lecture 31: Estimation Theory, Interval Estimation, Point Estimation

• School: University of Calgary
• Department: Statistics
• Course: STAT 213
• Professor: Anatoliy Swishchuk

Document Summary

The purpose of statistics: to permit the user to make an inference about a population based on information contained in a sample. Populations are characterized by numerical descriptive measures called parameters. Most statistical inference procedures involve either estima- tion or hypothesis testing. In this lecture 31 we consider the general topic of estimation of population parameters, point estimation and inter- val estimation. Examples of parameter estimation: mean value: , variance: 2, standard deviation: , probability of success: p, etc. Types of estimation: point estimation (a single value or point is given as the estimate of a parameter), interval estimation (two values are given to construct an interval that includes the parameter of interest). De nition of esimator: an estimator is a rule that tells how to cal- culate the value of an estimate based on the measurements contained in a sample. An estimator is most frequently expressed as a formula. Example 1: point esimator of the population mean value :