10.1
TESTS OF HYPOTHESES
An important area of inferential statistics is the testing of claims.
Examples:
Is the average volume of bottles for a particular brand of milk at least
128 ozs.?
Is a newly develop drug more effective at curing a disease than current
drugs on the market?
Do more than 50% of the people who will vote in the next election favor
passage of a bond issue?
To test these claims we have a statistical procedure called hypothesis
testing.
We start by forming a claim called the
null hypothesis (Ho)
.
The term null comes from concept that this claim is typically a statement
of no difference or no effect.
For example, we may state that μ = 128
ozs. (i.e.there is no difference between the advertised values of 128
ozs. and the true mean μ.)
In conjunction with the null hypothesis we form another hypothesis called
the
alternative hypothesis (Ha)
.
The alternative hypothesis is what we
suspect is true.
When the observed data is very unlikely to occur if the null hypothesis
is true we can conclude that the one of the following must be true:
1) The null hypothesis is true and we observed a rare set of data, or
2) The null hypothesis is false
Example:
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 Fall '10
 RaySievers
 Statistics, Inferential Statistics, Normal Distribution, Null hypothesis, Statistical hypothesis testing

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