t test, because the z test requires knowing the population standard deviation and that's rare. The t test embodies an estimate of the standard deviation.
It depends on the population.Use t-test for a small population, N < 30; otherwiase, apply z-test or when N>=30.
You use a z test when you are testing a hypothesis that is using proportions You use a t test when you are testing a hypothesis that is using means
If the sample size is less then 30 use the T table, if greater then 30 use the Z table.
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no t test is similar to z test because t test ie used for unknown observation and z is for the medicne
t test, because the z test requires knowing the population standard deviation and that's rare. The t test embodies an estimate of the standard deviation.
a t test is used inplace of a z-test when the population standard deviation is unknown.
It depends on the population.Use t-test for a small population, N < 30; otherwiase, apply z-test or when N>=30.
You use a z test when you are testing a hypothesis that is using proportions You use a t test when you are testing a hypothesis that is using means
The answer depends on whether the test is one-tailed or two-tailed.One-tailed: z = 1.28 Two-tailed: z = 1.64
z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.
If the sample size is less then 30 use the T table, if greater then 30 use the Z table.
The Z-value for a one-sided 91% confidence interval is 1.34
When we use a z-test, we know the population mean and standard deviation. When we use a t-test, we do not know the population standard deviation and thus must estimate this using the sample data that we have collected. If you look at your z-table and t-table, tcrit for df(infinity) = zcrit because at df(infinity) we would have an entire population and no longer need an estimate.
When the sample size is greater than 30
When the sample size is greater than 30