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Z-test
Explanations > Social Research > Analysis > Z-test Description | Discussion | See also
DescriptionThe Z-test compares sample and population means to determine if there is a significant difference. It requires a simple random sample from a population with a Normal distribution and where where the mean is known. CalculationThe z measure is calculated as: z = (x - m) / SE where x is the mean sample to be standardized, m (mu) is the population mean and SE is the standard error of the mean. SE = s / SQRT(n) where s is the population standard deviation and n is the sample size. The z value is then looked up in a z-table. A negative z value means it is below the population mean (the sign is ignored in the lookup table). DiscussionThe Z-test is typically with standardized tests, checking whether the scores from a particular sample are within or outside the standard test performance. The z value indicates the number of standard deviation units of the sample from the population mean. Note that the z-test is not the same as the z-score, although they are closely related. See also |
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| Home | Top | Quick Links | Settings | |
Main sections: | Disciplines | Techniques | Principles | Explanations | Theories | |
Other sections: | Blog! | Quotes | Guest articles | Analysis | Books | Help | |
More pages: | Contact | Caveat | About | Students | Webmasters | Awards | Guestbook | Feedback | Sitemap | Changes | |
Settings: | Computer layout | Mobile layout | Small font | Medium font | Large font | Translate | |
| Home | Top | Menu | Quick Links | |
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