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Is a t-test a parametric study?
Yes, it is. The one sample t-test is a study of the parameter population-mean. You can also use the t-test to test for the difference between two population means (both parameters).
How do you decide whether to use a z test or a t test when testing a hypothesis about a population mean?
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
When to use t-test?
You use the t-test when the population standard deviation is not known and estimated by the sample standard deviation. (1) To test hypothesis about the population mean (2) To test whether the means of two independent samples are different. (3) To test whether the means of two dependent samples are different. (4) To construct a confidence interval for the population mean.
How does the formula for the t test differ from the formula for the z test?
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.
What is a t-test?
a t test is used inplace of a z-test when the population standard deviation is unknown.
When do you use a z-value rejection region when testing a claim about a population mean?
If you know the population variance or if you have a very large sample then you could reliably use a Z test. Otherwise you should use a t test and use s^2 as an estimator for the population variance.
Is a z test or t test used more often?
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.
What conditions are necessary in order to use a t-test to test the differences between two population means?
The samples must be randomly selected, independent, and normally distributed. The following are necessary to use a t-test for small independent samples. 1. The samples must be randomly selected. 2. The samples must be independent. 3. Each population must have a normal distribution.
What is the difference between t test and z test in hypothesis testing?
It depends on the population.Use t-test for a small population, N < 30; otherwiase, apply z-test or when N>=30.
Why do you use the t test for the independent sample?
Because under the null hypothesis of no difference, the appropriate test statistic can be shown to have a t-distribution with the relevant degrees of freedom. So you use the t-test to see how well the observed test statistic fits in with a t-distribution.
What are the assumptions underlying the two sample t test?
The assumptions of a two-sample t-test are: Each sample come from a normally distributed population. Both populations have equal variances. The data are sampled independently from each population.
What conditions are necessary in order to use a test to test the differences between two population means?
The samples must be randomly selected, independent, and normally distributed. The following are necessary to use a t-test for small independent samples. 1. The samples must be randomly selected. 2. The samples must be independent. 3. Each population must have a normal distribution.
