Difference between revisions of "Z test"
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| − | The '''Z-test''' is a [[statistical test]] used in inference which determines if the difference between a sample mean and the population mean is large enough to be statistically significant. | + | The '''Z-test''' is a [[statistics|statistical test]] used in inference which determines if the difference between a sample mean and the population mean is large enough to be statistically significant. |
The Z-test is conducted by the following steps: | The Z-test is conducted by the following steps: | ||
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The Z-score is then compared to a Z-table. The Z-table indicates whether the calculated z-score is within the realm of chance or if the z-score is so different that the sample mean is unlikely to have happened by chance. | The Z-score is then compared to a Z-table. The Z-table indicates whether the calculated z-score is within the realm of chance or if the z-score is so different that the sample mean is unlikely to have happened by chance. | ||
| − | [[Category: | + | |
| + | [[Category:Statistics]] | ||
Latest revision as of 20:13, October 14, 2008
The Z-test is a statistical test used in inference which determines if the difference between a sample mean and the population mean is large enough to be statistically significant.
The Z-test is conducted by the following steps:
First the standard error of the mean is calculated:
- <math>\mathrm{SE} = \frac{\sigma}{\sqrt n}</math>
Then the formula for the Z-score for the Z-test is calculated by the formula:
- <math>z = \frac{x-\mu}{\mathrm{SE}}</math>
The Z-score is then compared to a Z-table. The Z-table indicates whether the calculated z-score is within the realm of chance or if the z-score is so different that the sample mean is unlikely to have happened by chance.