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## Chapter 7 Notes

by: Kaley Manspeaker

29

0

2

# Chapter 7 Notes k300

Kaley Manspeaker
IUPUI
GPA 3.8

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These notes include definitions for chapter 7.
COURSE
Elementary Statistics
PROF.
Curtis Ramsey
TYPE
Class Notes
PAGES
2
WORDS
CONCEPTS
Statistics
KARMA
25 ?

## Popular in Stats

This 2 page Class Notes was uploaded by Kaley Manspeaker on Friday March 4, 2016. The Class Notes belongs to k300 at Indiana University Purdue University - Indianapolis taught by Curtis Ramsey in Spring 2016. Since its upload, it has received 29 views. For similar materials see Elementary Statistics in Stats at Indiana University Purdue University - Indianapolis.

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Date Created: 03/04/16
Elementary Statistics Chapter 7 Definitions Definitions:  Point Estimate- is a specific numerical value estimate of a parameter.  Interval Estimate- Is an interval or a range of values used to estimate the parameter. This estimate may or may not contain the value of the parameter being estimated.  Confidence level- is the probability that the interval estimate will contain the parameter, assuming that a large number of samples are selected and that the estimation process on the same parameter is repeated.  Confidence Interval- Is a specific interval estimate of a parameter determined by using data obtained from a sample and by using the specific confidence level of the estimate.  Margin of Error- also called the maximum error of the estimate, is the maximum likely difference between the point estimate of parameter and the actual value of the parameter. Three Properties of a Good Estimator: 1. The estimator should be an unbiased estimator. That is, the expected value or the mean of the estimates obtained from samples of a given size is equal to the parameter being estimated. 2. The estimator should be consistent. For a consistent estimator, as sample size increases, the value of the estimator approaches the value of the parameter estimated. 3. The estimator should be a relatively efficient estimator. That is, of all the statistics that can be used to estimate a parameter, the relatively efficient estimator has the smallest variance.

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