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In statistics, Welch's t-test, or unequal variances t-test, is a two-sample location test which is used to test the (null) hypothesis that two populations have equal means. It is named for its creator, Bernard Lewis Welch , and is an adaptation of Student's t -test , [ 1 ] and is more reliable when the two samples have unequal variances and ...
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Print/export Download as PDF; ... Welch's t-test: interval: normal: unpaired: 2: No [8] ... This page was last edited on 5 July 2024, ...
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BTW, it makes sense to apply Welch's test routinely. If sample sizes are equal and variances are identical the result matches the conventional t-test. Therefore, in R by default Welch’s test is applied: t.test(data1, data2, alternative="two.sided") is equivalent to t.test(data1, data2, alternative="two.sided", var.equal=FALSE) One has to state
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[[Category:Time, date and calendar templates]] to the <includeonly> section at the bottom of that page. Otherwise, add <noinclude>[[Category:Time, date and calendar templates]]</noinclude> to the end of the template code, making sure it starts on the same line as the code's last character.
If there is interest in the marginal probability of obtaining a tail, only the number T out of the 100 flips that produced a tail needs to be recorded. But T can also be used as a test statistic in one of two ways: the exact sampling distribution of T under the null hypothesis is the binomial distribution with parameters 0.5 and 100.
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