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A home range is the area in which an animal lives and moves on a periodic basis. It is related to the concept of an animal's territory which is the area that is actively defended. The concept of a home range was introduced by W. H. Burt in 1943.
The choice of the test depends on many properties of the research question. The vast majority of studies can be addressed by 30 of the 100 or so statistical tests in use . [ 3 ] [ 4 ] [ 5 ]
In statistics, probability theory, and information theory, a statistical distance quantifies the distance between two statistical objects, which can be two random variables, or two probability distributions or samples, or the distance can be between an individual sample point and a population or a wider sample of points.
Additionally, the change to 0.005 would increase the likelihood of false negatives, whereby the effect being studied is real, but the test fails to show it. [ 63 ] In 2019, over 800 statisticians and scientists signed a message calling for the abandonment of the term "statistical significance" in science, [ 64 ] and the ASA published a further ...
A very simple equivalence testing approach is the ‘two one-sided t-tests’ (TOST) procedure. [11] In the TOST procedure an upper (Δ U) and lower (–Δ L) equivalence bound is specified based on the smallest effect size of interest (e.g., a positive or negative difference of d = 0.3).
The studentized test enjoys optimal properties as the statistic that is bootstrapped is pivotal (i.e. it does not depend on nuisance parameters as the t-test follows asymptotically a N(0,1) distribution), unlike the percentile bootstrap. Bias-corrected bootstrap – adjusts for bias in the bootstrap distribution.
Sørensen's original formula was intended to be applied to discrete data. Given two sets, X and Y, it is defined as = | | | | + | | where |X| and |Y| are the cardinalities of the two sets (i.e. the number of elements in each set). The Sørensen index equals twice the number of elements common to both sets divided by the sum of the number of ...
This ensures that the hypothesis test maintains its specified false positive rate (provided that statistical assumptions are met). [35] The p-value is the probability that a test statistic which is at least as extreme as the one obtained would occur under the null hypothesis. At a significance level of 0.05, a fair coin would be expected to ...