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The following table defines the possible outcomes when testing multiple null hypotheses. Suppose we have a number m of null hypotheses, denoted by: H 1, H 2, ..., H m. Using a statistical test, we reject the null hypothesis if the test is declared significant. We do not reject the null hypothesis if the test is non-significant.
This is why the hypothesis under test is often called the null hypothesis (most likely, coined by Fisher (1935, p. 19)), because it is this hypothesis that is to be either nullified or not nullified by the test. When the null hypothesis is nullified, it is possible to conclude that data support the "alternative hypothesis" (which is the ...
In some programming language environments (at least one proprietary Lisp implementation, for example), [citation needed] the value used as the null pointer (called nil in Lisp) may actually be a pointer to a block of internal data useful to the implementation (but not explicitly reachable from user programs), thus allowing the same register to be used as a useful constant and a quick way of ...
To expose dangling pointer errors, one common programming technique is to set pointers to the null pointer or to an invalid address once the storage they point to has been released. When the null pointer is dereferenced (in most languages) the program will immediately terminate—there is no potential for data corruption or unpredictable behavior.
A null pointer has a value reserved for indicating that the pointer does not refer to a valid object. Null pointers are routinely used to represent conditions such as the end of a list of unknown length or the failure to perform some action; this use of null pointers can be compared to nullable types and to the Nothing value in an option type.
In scientific research, the null hypothesis (often denoted H 0) [1] is the claim that the effect being studied does not exist. [note 1] The null hypothesis can also be described as the hypothesis in which no relationship exists between two sets of data or variables being analyzed. If the null hypothesis is true, any experimentally observed ...
Null distribution is a tool scientists often use when conducting experiments. The null distribution is the distribution of two sets of data under a null hypothesis. If the results of the two sets of data are not outside the parameters of the expected results, then the null hypothesis is said to be true. Null and alternative distribution
The following table defines the possible outcomes when testing multiple null hypotheses. Suppose we have a number m of null hypotheses, denoted by: H 1, H 2, ..., H m. Using a statistical test, we reject the null hypothesis if the test is declared significant. We do not reject the null hypothesis if the test is non-significant.