Search results
Results From The WOW.Com Content Network
The p-values of the rejected null hypothesis (i.e. declared discoveries) are colored in red. Note that there are rejected p-values which are above the rejection line (in blue) since all null hypothesis of p-values which are ranked before the p-value of the last intersection are rejected. The approximations MFDR = 0.02625 and AFDR = 0.00730, here.
A hypothesis is rejected at level α if and only if its adjusted p-value is less than α. In the earlier example using equal weights, the adjusted p-values are 0.03, 0.06, 0.06, and 0.02. This is another way to see that using α = 0.05, only hypotheses one and four are rejected by this procedure.
The Bonferroni correction can also be applied as a p-value adjustment: Using that approach, instead of adjusting the alpha level, each p-value is multiplied by the number of tests (with adjusted p-values that exceed 1 then being reduced to 1), and the alpha level is left unchanged.
Hochberg's step-up procedure (1988) is performed using the following steps: [7] Start by ordering the p-values (from lowest to highest) () … and let the associated hypotheses be …
The solution to this question would be to report the p-value or significance level α of the statistic. For example, if the p-value of a test statistic result is estimated at 0.0596, then there is a probability of 5.96% that we falsely reject H 0. Or, if we say, the statistic is performed at level α, like 0.05, then we allow to falsely reject ...
In null-hypothesis significance testing, the p-value [note 1] is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. [2] [3] A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis.
"The value for which P = .05, or 1 in 20, is 1.96 or nearly 2; it is convenient to take this point as a limit in judging whether a deviation is to be considered significant or not." [11] In Table 1 of the same work, he gave the more precise value 1.959964. [12] In 1970, the value truncated to 20 decimal places was calculated to be
The value q s is the sample's test statistic. (The notation | x | means the absolute value of x; the magnitude of x with the sign set to +, regardless of the original sign of x.) This q s test statistic can then be compared to a q value for the chosen significance level α from a table of the studentized range distribution.