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Difference between Z-test and t-test: Z-test is used when sample size is large (n>50), or the population variance is known. t-test is used when sample size is small (n<50) and population variance is unknown. There is no universal constant at which the sample size is generally considered large enough to justify use of the plug-in test.
Isn't 'z-test' more or less a synonym for 'Wald test'? I think mathematical-statistical texts would prefer the latter, but less technical sources may prefer the former. I guess 'Wald test' only applies when the estimate is obtained by maximum likelihood though. Should we consider merging the two articles? Qwfp 08:48, 22 February 2011 (UTC)
The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]
Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.
Statistical tests are used to test the fit between a hypothesis and the data. [1] [2] Choosing the right statistical test is not a trivial task. [1]The choice of the test depends on many properties of the research question.
A printed quiz on health issues. A quiz is a form of mind sport in which players attempt to answer questions correctly on one or several topics. Quizzes can be used as a brief assessment in education and similar fields to measure growth in knowledge, abilities, and skills, or simply as a hobby.
A multiple-choice test provides the test taker with questions paired with a pre-determined list of possible answers. It is a type of closed-ended question . The test taker chooses the correct answer from the list.
A normal quantile plot for a simulated set of test statistics that have been standardized to be Z-scores under the null hypothesis. The departure of the upper tail of the distribution from the expected trend along the diagonal is due to the presence of substantially more large test statistic values than would be expected if all null hypotheses were true.
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