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![Student's t-test - Wikipedia, the free encyclopedia]()
en.wikipedia.orgA t-test is any statistical hypothesis test in which the test statistic follows a .... has a t-distribution with n − 2 degrees of freedom if the null hypothesis is true.瀏覽：885 -
![Tests of Significance - Welcome | Department of Statistics]()
www.stat.yale.eduSignificance Tests for Unknown Mean and Known Standard Deviation Once null and alternative hypotheses ...瀏覽：614
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日期：2024-08-29
The significance level for a given hypothesis test is a value for which a P-value
less than .... The test statistic follows the t distribution with n-1 degrees of freedom
....
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日期：2024-09-05
The t-test produces a single value, t, which grows larger as the difference
between the ... Each t-value is in a column that is specific to a given significance
level....
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日期：2024-09-03
pdf version of this page In this review, we'll look at significance testing, using
mostly the t-test as a guide. As you read educational research, you'll encounter ......
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日期：2024-09-04
In simple terms, the t-test compares the actual difference between two means in
... In biological work we accept this level of significance as being reasonable....
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日期：2024-08-30
To use the table it is important to note that the t-distribution is symmetrical. ...
testing), and they are the values that run along the horizontal line of the t ... up the
critical values, and to do this week need both df and the significance leve...
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日期：2024-09-01
How to Use This Table, This table contains critical values of the Student's t
distribution ... The significance level, α, is demonstrated in the graph below,
which displays a t ... If the absolute value of the test statistic is greater than the
c...
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日期：2024-09-04
1 History 2 Role in statistical hypothesis testing 3 Defining significance in terms of sigma (σ) 4 Effect size 5 See also 6 References 7 Further reading ... The concept of statistical significance was originated by Ronald Fisher when he developed statisti...
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日期：2024-09-04
In statistical significance testing, the p-value is the probability of obtaining a test statistic result at least as extreme as the one that was actually observed, assuming that the null hypothesis is true.[1][2] A researcher will often "reject the null h...
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