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What is the difference between the goodness of fit test and the contingency test?
Wiki User
∙ 11y ago
Goodness of fit test is used to test a single population. The null hypothesis will be that the observed frequencies are equal to expected frequencies (based on computed intrinsic values given the extrinsic values).
A good example would be comparing observed phenotype frequencies against expected frequencies calculated from the parental genotypes (Simple dominance gives rise to 1:2:1 ratio with two parental heterozygotes).
Contingency test is used to see whether or not different populations are associated. The null hypothesis will be that that different populations are independent of one another.
A good example would be comparing the effect of different host plants on different populations of insects. (Effect of Host A on Insect population 1, 2, 3; Effect of Host B on Insect population 1, 2, 3; etc)
Wiki User
∙ 11y ago
The goodness of fit test is used to determine if a sample comes from a specific population by comparing the observed frequencies to the expected frequencies. It is used to test if there is a significant difference between the observed data and the expected data.
On the other hand, the contingency test, also known as the chi-square test of independence, is used to determine if there is an association between two categorical variables by comparing the observed frequencies in a contingency table to the frequencies that would be expected if the variables were independent. It is used to assess if there is a significant relationship between the two variables.
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When is the chi-test used?
There are many chi-squared tests. You may mean the chi-square goodness-of-fit test or chi-square test for independence. Here is what they are used for.A test of goodness of fit establishes if an observed frequency differs from a theoretical distribution.A test of independence looks at whether paired observations on two variables, expressed in a contingency table, are independent of each.
How to get expected frequency value in chi square test?
For goodness of fit test using Chisquare test, Expected frequency = Total number of observations * theoretical probability specified or Expected frequency = Total number of observations / Number of categories if theoretical frequencies are not given. For contingency tables (test for independence) Expected frequency = (Row total * Column total) / Grand total for each cell
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There are many chi-squared tests. You may mean the chi-square goodness-of-fit test or chi-square test for independence. Here is what they are used for.A test of goodness of fit establishes if an observed frequency differs from a theoretical distribution.A test of independence looks at whether paired observations on two variables, expressed in a contingency table, are independent of each.
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