Search results
Results From The WOW.Com Content Network
Paired samples t-tests typically consist of a sample of matched pairs of similar units, or one group of units that has been tested twice (a "repeated measures" t-test). A typical example of the repeated measures t -test would be where subjects are tested prior to a treatment, say for high blood pressure, and the same subjects are tested again ...
Unpaired samples are also called independent samples. Paired samples are also called dependent. Finally, there are some statistical tests that perform analysis of relationship between multiple variables like regression. [1] Number of samples: The number of samples of data. Exactness: A test can be exact or be asymptotic delivering approximate ...
If the test is performed using the actual population mean and variance, rather than an estimate from a sample, it would be called a one-tailed or two-tailed Z-test. The statistical tables for t and for Z provide critical values for both one- and two-tailed tests. That is, they provide the critical values that cut off an entire region at one or ...
A one-tailed hypothesis (tested using a one-sided test) [2] is an inexact hypothesis in which the value of a parameter is specified as being either: above or equal to a certain value, or; below or equal to a certain value. A one-tailed hypothesis is said to have directionality. Fisher's original (lady tasting tea) example was a one-tailed test ...
The one-sample version serves a purpose similar to that of the one-sample Student's t-test. [2] For two matched samples, it is a paired difference test like the paired Student's t -test (also known as the " t -test for matched pairs" or " t -test for dependent samples").
the value of T can be compared with its expected value under the null hypothesis of 50, and since the sample size is large, a normal distribution can be used as an approximation to the sampling distribution either for T or for the revised test statistic T−50. Using one of these sampling distributions, it is possible to compute either a one ...
The Student's t distribution plays a role in a number of widely used statistical analyses, including Student's t test for assessing the statistical significance of the difference between two sample means, the construction of confidence intervals for the difference between two population means, and in linear regression analysis.
Most frequently, t statistics are used in Student's t-tests, a form of statistical hypothesis testing, and in the computation of certain confidence intervals. The key property of the t statistic is that it is a pivotal quantity – while defined in terms of the sample mean, its sampling distribution does not depend on the population parameters, and thus it can be used regardless of what these ...