Lecture_19,_Chap_10,_Sec_1

# Lecture_19,_Chap_10,_Sec_1 - Chapter 10 Testing Claims...

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Chapter 10 Testing Claims Regarding a Parameter

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Overview This is the other part of inferential statistics, hypothesis testing Hypothesis testing and estimation are two different approaches to two similar problems Estimation is the process of using sample data to estimate the value of a population parameter Hypothesis testing is the process of using sample data to test a claim about the value of a population parameter
Chapter 10 Section 1 The Language of Hypothesis Testing

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Chapter 10 – Section 1 Learning objectives Determine the null and alternative hypotheses from a claim Understand Type I and Type II errors State conclusions to hypothesis tests 1 2 3
Hypothesis Testing The environment of our problem is that we want to test whether a particular claim is believable, or not The process that we use is called hypothesis testing This is one of the most common goals of statistics

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Hypothesis Testing Hypothesis testing involves two steps Step 1 – to state what we think is true Step 2 – to quantify how confident we are in our claim The first step is relatively easy The second step is why we need statistics
Hypothesis Testing We are usually told what the claim is, what the goal of the test is Now similar to estimation in the previous chapter, we will again use the material in Chapter 8 on the sample mean to quantify how confident we are in our claim

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Hypothesis Testing An example of what we want to quantify A car manufacturer claims that a certain model of car achieves 29 miles per gallon We test some number of cars We calculate the sample mean … it is 27 Is 27 miles per gallon consistent with the manufacturer’s claim? How confident are we that the manufacturer has significantly overstated the miles per gallon achievable?
Hypothesis Testing A hypothesis test for an unknown parameter is a test of a specific claim Compare this to a confidence interval which gives an interval of numbers, not a “believe it” or “don’t believe it” answer for an unknown parameter is a Compare this to a confidence interval which gives an interval of numbers, not a “believe it” or “don’t believe it” answer Since a claim can either be true or false, hypothesis testing is based on two types of hypotheses

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Hypothesis Testing The null hypothesis is a statement to be tested It is a statement regarding the value of a population parameter It is a statement of status quo or no difference It always contains a statement of equality It assumed to be true until we have evidence to the contrary It is written as H 0 (read as “H-naught” or “H-sub-Oh”)
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## This note was uploaded on 08/04/2008 for the course STAT 250 taught by Professor Sims during the Spring '08 term at George Mason.

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Lecture_19,_Chap_10,_Sec_1 - Chapter 10 Testing Claims...

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