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- TEST STATISTICS
- A random variable that is calculated from sample data used in a hypothesis test is called a test statistic..
- Before you can find the test statistic (z or t-test), you need to think about whether the population standard deviation is known or unknown..
- Z-TEST- is employed to verify a claim that the population from which the sample was drawn is the same
- Use the z-test when the variance is known, the distribution is normal, or the sample size is big (n is larger than or equal to 30).
- A z-test presumes that the sample is regularly distributed. Population parameters like the population mean and standard deviation are used to construct a z-score .
- SUMMARIZATION
- T-TEST- employed when standard deviation or population variance are unknown
- A t-test, on the other hand, makes the same assumption about the sample's normal distribution as a z-test.
- Use a t-test when the variance is unknown and the sample size is less than 30 (n 30). Assume that the population is distributed normally or nearly so.
- CENTRAL LIMIT THEOREM (CLT)- If the sample size is big, the population is normally distributed, and the true population mean is u=u0, then z has a typical normal distribution.
- By substituting the sample standard deviation for the population standard deviation in the formula, we may still utilize the z-test and z-score when the variance is unknown.
- The CLT is employed in some circumstances. In CLT, the sample size must be more than or equal to 30, the population may not be normally distributed, and the variance may be known or unknown.
- population standard deviation is known
- n is greater that or equal to 30
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- z-test
- population standard deviation is unknown
- When the value of sample size (n)...
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- To have a better understanding of the lesson. Let's take a look at this...
- population standard deviation is known
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- z-test
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- n is less than 30
- population standard deviation is unknown
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- t-test
- Now, that is how you can identify the appropriate test statistics involving population mean.
- Thank you sir!
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