Week Three Lecture – Part II
This week let’s continue to discuss chisquare and focus on the equal expected
frequencies. This will be a brief lecture because this application of chisquare is very
simple. In Week Three, we are examining and applying chisquare as a “Goodnessof
Fit.”
This form of chisquare is commonly used to test the significance of expected
frequencies. The goodness of fit test is one of the most commonly used nonparametric
tests.
Let’s look at chisquare as a test with equal expected frequencies. The ebook
describes the utility of this form of test as a nonparametric application. As we also know,
nonparametric data are nominal and ordinal data. According, these data are free from
assumptions regarding the shape of the population, and are distribution free tests.
The chisquare testing procedure is the same as the test sequence for z and t. The
formula for this form of chisquare testing is:
x
2
=
∑
[ (fo –fe)
2
]
fe
with
k – 1 degrees of freedom where:
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 Spring '10
 Regis
 Statistics, Null hypothesis, Statistical hypothesis testing, Statistical significance, Chisquare distribution, chisquare testing

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