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If we use the test statistic /, then under the null hypothesis is exactly 1 for two-sided p-value, and exactly / for one-sided left-tail p-value, and same for one-sided right-tail p-value. If we consider every outcome that has equal or lower probability than "3 heads 3 tails" as "at least as extreme", then the p -value is exactly 1 / 2 ...
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 ...
If we control the pFDR to 0.05 by considering all genes with a q-value of less than 0.05 to be differentially expressed, then we expect 5% of the positive results to be false positives (e.g. 900 true positives, 45 false positives, 100 false negatives, 8,955 true negatives). This strategy enables one to obtain relatively low numbers of both ...
In the above, the number of independent random variables in the sequence is fixed. Assume N {\displaystyle N} is discrete random variable taking values on the non-negative integers, which is independent of the X i {\displaystyle X_{i}} , and consider the probability generating function G N {\displaystyle G_{N}} .
Note: Fisher's G-test in the GeneCycle Package of the R programming language (fisher.g.test) does not implement the G-test as described in this article, but rather Fisher's exact test of Gaussian white-noise in a time series. [10] Another R implementation to compute the G statistic and corresponding p-values is provided by the R package entropy.
In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own Boolean-valued outcome: success (with probability p) or failure (with probability q = 1 − p).
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For example, if P(x) is the predicate "x is greater than 0 and less than 1", then, for a domain of discourse X of all natural numbers, the existential quantification "There exists a natural number x which is greater than 0 and less than 1" can be symbolically stated as: ()