Chi Square Test

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Psychology
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Capella University
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Chi-Square Test
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Chi-Square Test
The Chi-Square goodness of fit test is a type of statistical test used to determine how an
observed value differs from the expected or theoretical value. The term goodness of fit refers to
the comparison between the observed sample distribution and the theoretical probability
distribution. This test is used to show how well theoretical distribution fits the empirical
distribution. In other words, it checks whether the sample data may be from a certain theoretical
distribution. When using the goodness of fit test, one needs one variable and a hypothesis of how
the variable is distributed.
Both the Chi-square goodness of fit test and simple frequency distribution are used to
determine how frequently direct variables will occur in research. However, while simple
frequency distribution will reveal the frequency of the occurrence of a phenomenon or item, the
Chi-Square goodness of fit test involves the use of those direct values to determine the exact
frequency of occurrence.
The Chi-Square test of independence is a hypothesis test used in statistics to determine
the relationship between two categorical or nominal variables (whether they are related or not).
This test is used when there are counts for two categorical variables. The Chi-Square test of
independence can also be used when there is only a table of frequency counts. To use this test,
one needs two variables. The idea here is that they are not related. The Chi-Square test of
independence requires two variables in comparison to the Chi-Square goodness of fit test which
requires only one variable. While the goodness of fit test seeks to determine the uniformity of a
population, the test of independence is used to check whether two variables are related or not.
Both tests are used to decode relationships between observed sets of data and expected sets of
data that relate to the null hypothesis.

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1 Chi-Square Test Name: Department: Course Name: Instructor: Date: 2 Chi-Square Test The Chi-Square goodness of fit test is a type of statistical test used to determine how an observed value differs from the expected or theoretical value. The term goodness of fit refers to the comparison between the observed sample distribution and the theoretical probability distribution. This test is used to show how well theoretical distribution fits the empirical distribution. In other words, it checks whether the sample data may be from a certain theoretical distribution. When using the goodness of fit test, one needs one variable and a hypothesis of how the variable is distributed. Both the Chi-square goodness of fit test and simple frequency distribution are used to determine how frequently direct variables will occur in research. However, while simple frequency distribution will reveal the frequency of the occurrence of a phenomenon or item, the Chi-Square goodness of fit test involves the use of those direct values to determine the exact frequency of occurrence. The Chi-Square test of independence is a hypothesis test used in statistics to determine the relationship between two categor ...
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