CHI-SQUARE GOODNESS
OF FIT TEST
What Are
Nonparametric
Statistics?
What is the Purpose of
the Chi-Square GOF?
What Are the
Assumptions?
How Does it Work?
What Are
Nonparametric Statistics?
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Statistical tests such as the t-test and ztest are parametric because they test a
hypothesis about a particular
population value (parameter).
Nonparametrics such as chi-square test
a hypothesis, but not about one
particular parameter.
What Are
Nonparametric Statistics?
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Parametric statistics require
assumptions that are often not satisfied
(e.g., shape of the population
distribution, interval/ratio data).
Nonparametric statistics require
assumptions, but they are easier to
meet.
What is the Purpose of the
Chi-Square Goodness of Fit?
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Test whether an observed frequency
distribution differs from a Null
Hypothesis frequency distribution.
Use for a design in which individuals
are categorized into two or more
groups.
What are the Assumptions?
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mutually exclusive groups
expected frequencies at least 5 per cell
How Does it Work?
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Determine the frequencies you expect
if the Ho is true.
Compare the observed frequencies to
the Ho expected frequencies.
Large differences between observed
and expected give a large value of chisquare, likely to be significant.