Search results
Results from the WOW.Com Content Network
See also: the {{}} template. The #if function selects one of two alternatives based on the truth value of a test string. {{#if: test string | value if true | value if false}} As explained above, a string is considered true if it contains at least one non-whitespace character.
In mathematics, an inequation is a statement that an inequality holds between two values. [1] [2] It is usually written in the form of a pair of expressions denoting the values in question, with a relational sign between them indicating the specific inequality relation.
≠ (not-equal sign) Denotes inequality and means "not equal". ≈ The most common symbol for denoting approximate equality. For example, ~ 1. Between two numbers, either it is used instead of ≈ to mean "approximatively equal", or it means "has the same order of magnitude as". 2.
Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Help; Learn to edit; Community portal; Recent changes; Upload file
These results are not subject to round-off error, but they are not accurate unless b 2 is large compared to ac. Excel graph of the difference between two evaluations of the smallest root of a quadratic: direct evaluation using the quadratic formula (accurate at smaller b) and an approximation for widely spaced roots (accurate for larger b). The ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.
The relation not greater than can also be represented by , the symbol for "greater than" bisected by a slash, "not". The same is true for not less than, . The notation a ≠ b means that a is not equal to b; this inequation sometimes is considered a form of strict inequality. [4]
O i = an observed count for bin i; E i = an expected count for bin i, asserted by the null hypothesis. The expected frequency is calculated by: = (() ()) where: F = the cumulative distribution function for the probability distribution being tested. Y u = the upper limit for bin i,