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Chapter 11

MGMT 1050 Chapter 11: CH 11 Notes


Department
Management
Course Code
MGMT 1050
Professor
Olga Kraminer
Chapter
11

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Chapter 11
Defining Hypothesis Testing
- Hypothesis testing is a statistical procedure that is used to determine whether an
idea or a guess is correct or not
Two types of hypotheses
1. Null hypothesis
2. Alternate hypothesis
Hypothesis Testing Errors
- A type 1 error occurs when we reject a true null hypothesis (the defendant is
innocent and we convict them
- A type 2 error occurs when we not reject a false null hypothesis (ex. The defendant
is guilty and we do not convict them)
- The probability of type 1 error is denoted as α, the sigifiae leel
- The probability of a type 2 error is denoted as β
Writing Hypotheses
- The purpose of hypothesis testing is to verify if your guess about a population is true
- For instance, we use the value of a test statistic, to determine whether we should
reject the null hypothesis or not
Note the following properties about stating the hypothesis:
a) The null hypothesis always goes first and the alternate always goes second
b) The variable after the null hypothesis is always a parameter (since we are trying to
see if our conclusion about a population is correct, it is important we put a
parameter in the statement since parameters describe a population) watch out for
tricks in m/c that use statistics and ask you if the hypothesis is correctly written
c) The null hypothesis always has the statement that is assumed to be true unless
otherwise proven while the alternative has what we are testing for (looking for
evidence to support)
d) The null hypothesis has an equality in it
e) The alternate hypothesis covers the range that the null hypothesis does not
(together they cover the entire number line so that they are mutually exclusive and
exhaustive)
The P-Value Approach
find more resources at oneclass.com
find more resources at oneclass.com
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