(a-b-test-statistic N-a n-a N-b n-b)
Calculates the statistic for the hypothesis, that p-a and p-b are the same, given the outcomes for test a and b.
Calculates the statistic for the hypothesis, that p-a and p-b are the same, given the outcomes for test a and b.
(correlation-coefficient coll1 coll2)
Returns the correlation coefficient for the collections coll1
and coll2
.
Returns the correlation coefficient for the collections `coll1` and `coll2`.
(covariance coll1 coll2)
Returns the biased sample covariance (n) for the collections coll1
and coll2
.
Returns the biased sample covariance (n) for the collections `coll1` and `coll2`.
(cubic-average coll)
Returns the cubic average of the values of the collection coll
.
Returns the cubic average of the values of the collection `coll`.
(de-mean coll)
Returns a collection with the mean substacted from each value of input collection coll
.
Returns a collection with the mean substacted from each value of input collection `coll`.
(de-mean-matrix m)
Returns a matrix with the column mean substacted from each value of input matrix m
.
Returns a matrix with the column mean substacted from each value of input matrix `m`.
(deviation coll)
Returns the biased sample deviation (n) for the collection coll
.
Returns the biased sample deviation (n) for the collection `coll`.
Returns the geometric average (mean) of the values of the collection coll
.
Returns the geometric average (mean) of the values of the collection `coll`.
(harmonic-average coll)
Returns the harmonic average of the values of the collection coll
.
Returns the harmonic average of the values of the collection `coll`.
(linear-regression coll1 coll2)
Returns a vector [a b] of the linear regession coefficients for the equation y = ax + b for the collections coll1
and coll2
.
Returns a vector [a b] of the linear regession coefficients for the equation y = ax + b for the collections `coll1` and `coll2`.
Returns the mean of the values of the collection coll
.
Returns the mean of the values of the collection `coll`.
(median coll)
Returns the median / second quartile for the collection coll
.
Returns the median / second quartile for the collection `coll`.
(q-value q coll)
Multiplies the count of coll
with q
.
Multiplies the count of `coll` with `q`.
(quantile q coll)
Returns the q
quantile for the collection coll
.
Returns the `q` quantile for the collection `coll`.
(quartile1 coll)
Returns the first quartile for the collection coll
.
Returns the first quartile for the collection `coll`.
(quartile2 coll)
Returns the second quartile / median for the collection coll
.
Returns the second quartile / median for the collection `coll`.
(quartile3 coll)
Returns the third quartile for the collection coll
.
Returns the third quartile for the collection `coll`.
(rescale m)
Rescales the matrix m
to have a mean of 0 and an unbiased standard deviation of 1.
Rescales the matrix `m` to have a mean of 0 and an unbiased standard deviation of 1.
(scale m)
Returns the mean vector and the unbiased standard deviation vector for the colums of the matrix m
.
Returns the mean vector and the unbiased standard deviation vector for the colums of the matrix `m`.
(square-average coll)
Returns the square average of the values of the collection coll
.
Returns the square average of the values of the collection `coll`.
(unbiased-covariance coll1 coll2)
Returns the unbiased sample covariance (n-1) for the collections coll1
and coll2
.
Returns the unbiased sample covariance (n-1) for the collections `coll1` and `coll2`.
(unbiased-deviation coll)
Returns the unbiased sample deviation (n-1) for the collection coll
.
Returns the unbiased sample deviation (n-1) for the collection `coll`.
(unbiased-variance coll)
Returns the unbiased sample variance (n-1) for the collection coll
.
Returns the unbiased sample variance (n-1) for the collection `coll`.
(variance coll)
Returns the biased sample variance (n) for the collection coll
.
Returns the biased sample variance (n) for the collection `coll`.
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