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Survival functions or complementary cumulative distribution functions are often denoted by placing an overbar over the symbol for the cumulative: ¯ = (), or denoted as (), In particular, the pdf of the standard normal distribution is denoted by φ ( z ) {\textstyle \varphi (z)} , and its cdf by Φ ( z ) {\textstyle \Phi (z)} .
Also, the characteristic function of the sample mean X of n independent observations has characteristic function φ X (t) = (e −|t|/n) n = e −|t|, using the result from the previous section. This is the characteristic function of the standard Cauchy distribution: thus, the sample mean has the same distribution as the population itself.
In probability theory and statistics, the F-distribution or F-ratio, also known as Snedecor's F distribution or the Fisher–Snedecor distribution (after Ronald Fisher and George W. Snedecor), is a continuous probability distribution that arises frequently as the null distribution of a test statistic, most notably in the analysis of variance (ANOVA) and other F-tests.
3. Restriction of a function: if f is a function, and S is a subset of its domain, then | is the function with S as a domain that equals f on S. 4. Conditional probability: () denotes the probability of X given that the event E occurs. Also denoted (/); see "/". 5.
With some standard function when there is little chance of ambiguity, it is common to omit the parentheses around the argument altogether (e.g., ). Note that this is never done with a general function f {\displaystyle f} , in which case the parenthesis are always included
If f(n) = n 2 + 3n, then as n becomes very large, the term 3n becomes insignificant compared to n 2. The function f(n) is said to be "asymptotically equivalent to n 2, as n → ∞". This is often written symbolically as f (n) ~ n 2, which is read as "f(n) is asymptotic to n 2". An example of an important asymptotic result is the prime number ...
Almost a century later, Leonhard Euler fixed the terminology of infinitesimal calculus, and introduced the notation y = f(x) for a function f, its variable x and its value y. Until the end of the 19th century, the word variable referred almost exclusively to the arguments and the values of functions.
The null hypothesis is rejected if the F calculated from the data is greater than the critical value of the F-distribution for some desired false-rejection probability (e.g. 0.05). Since F is a monotone function of the likelihood ratio statistic, the F-test is a likelihood ratio test.