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Categorical data, represent frequency distribution among different categories |
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most common method to represent trends over time |
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contains 67% of the values |
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Used to compare 2 sets of continuously distributed data Means of the 2 sets of data must be KNOWN |
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Used to compare two different sets of continuously distributed data with unknown means |
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Both normal distributions. Z-distribution is tighter; t-distribution is broader. T-tests require greater difference than z to be statistically significant |
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Test used when the Chi-Square is unstable due to small numbers. (Chi-Squared needs to have at least “1” in each cell and <20% of cells with <5.) |
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Analogous to t-tests, but with >2 samples. Assesses multiple independent populations. Used in laboratory studies when there are multiple measures |
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Test used when the t-test cells are <5. (If cells are 0, or 1, there is a major problem in calculating the results) (F-distribution is not normally distributed) |
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Test used when data are paired. Otherwise, analogous to the Chi-Square |
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