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STA 2023
Module 10
Hypothesis Tests for One
Population Mean
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Learning Objectives
Upon completing this module, you should be able to:
1.
Define the terms associated with hypothesis testing.
2.
Choose the null and alternative hypotheses for a hypothesis test.
3.
Explain the logic behind hypothesis testing.
4.
Identify the test statistic, rejection region, nonrejection region, and
critical value(s) for a hypothesis test.
5.
Define and apply the concepts of Type I and Type II errors.
6.
State and interpret the possible conclusions for a hypothesis test.
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Learning Objectives (cont.)
7.
Obtain the critical value(s) for a specified significance level.
8.
Perform a hypothesis test for a population mean when the population
standard deviation is known.
9.
Obtain the Pvalue of a hypothesis test.
10.
State and apply the steps for performing a hypothesis test, using the
criticalvalue approach to hypothesis testing.
11.
State and apply the steps for performing a hypothesis test, using the
Pvalue approach to hypothesis testing.
12.
Perform a hypothesis test for a population mean when the population
standard deviation is unknown.
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valenciacc
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How a Statistic is Used?
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In the previous module, we looked at methods for
obtaining the
confidence intervals for one population
mean.
We have learned that a
confidence interval for a
population mean
, is based on a sample mean (a
statistic).
In this module, we are going to look at how a
statistic
(sample mean) is used to make decisions about
hypothesized values of a
parameter
(population
mean.)
Rev.F08
5
Decision and Hypothesis Test
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One of the commonly used methods for making
decision is to perform a
hypothesis test
A
hypothesis test
involves two hypotheses:
the
null
hypothesis
and the
alternative hypothesis
.
“Testing a hypothesis” is like “testing a claim.”
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What are Hypotheses?
Hypotheses are working models that we adopt
temporarily.
Our starting hypothesis is called the
null hypothesis
.
The
null hypothesis
, that we denote by H
0
, specifies a
population model
parameter of interest
and proposes
a value for that
parameter
.
We usually write down the null hypothesis in the form
H
0
:
parameter
=
hypothesized
value
.
The
alternative hypothesis
, which we denote by H
A
,
contains the value of the
parameter
that we consider
plausible when we reject the null hypothesis.
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Testing Hypotheses
The first step in defining the null and alternative hypotheses is to
determine which parameter is being tested. A
parameter
describes a population.
Examples are the
population mean
, the
population standard deviation
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This note was uploaded on 06/14/2011 for the course STA 2023 taught by Professor Bagwhandee during the Spring '07 term at University of Central Florida.
 Spring '07
 Bagwhandee

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