171SB2_tut3_08
... Compare the estimated numbers with the actual numbers given above. Do you think the binomial model fits these data well? Give reasons why the binomial distribution might not be expected to fit the data particularly well. (Hint: Think how a disease spreads. If a given child is infected is it more or ...
... Compare the estimated numbers with the actual numbers given above. Do you think the binomial model fits these data well? Give reasons why the binomial distribution might not be expected to fit the data particularly well. (Hint: Think how a disease spreads. If a given child is infected is it more or ...
Permutation tests - People Server at UNCW
... distributions of test statistics are exact in the sense that they are not dependent upon unverified assumptions about the underlying population distribution ... • Approximate p-values may be obtained from random sampling of permutations and for large number of random samples, the error can be quite ...
... distributions of test statistics are exact in the sense that they are not dependent upon unverified assumptions about the underlying population distribution ... • Approximate p-values may be obtained from random sampling of permutations and for large number of random samples, the error can be quite ...
Fisher–Yates shuffle
The Fisher–Yates shuffle (named after Ronald Fisher and Frank Yates), also known as the Knuth shuffle (after Donald Knuth), is an algorithm for generating a random permutation of a finite set—in plain terms, for randomly shuffling the set. A variant of the Fisher–Yates shuffle, known as Sattolo's algorithm, may be used to generate random cyclic permutations of length n instead. The Fisher–Yates shuffle is unbiased, so that every permutation is equally likely. The modern version of the algorithm is also rather efficient, requiring only time proportional to the number of items being shuffled and no additional storage space.Fisher–Yates shuffling is similar to randomly picking numbered tickets (combinatorics: distinguishable objects) out of a hat without replacement until there are none left.