Convolution and correlation are central to many kinds of operations on lists of data. They are used in such areas as signal and image processing, statistical data analysis, ...

Integration functions. Here is the integral ∫_a^bx^2 dx. This gives the multiple integral ∫_0^adx ∫_0^bd y(x^2+y^2).

Descriptive statistics refers to properties of distributions, such as location, dispersion, and shape. The functions described here compute descriptive statistics of lists of ...

The functions described here are among the most commonly used discrete univariate statistical distributions. You can compute their densities, means, variances, and other ...

Minimization and maximization. Minimize and Maximize yield lists giving the value attained at the minimum or maximum, together with rules specifying where the minimum or ...

Output formats for numbers. These numbers are given in the default output format. Large numbers are given in scientific notation. This gives all numbers in scientific ...

CUDAImageAdd[img, x] adds an amount x to each channel value in img.CUDAImageAdd[mem, x] adds an amount x to each channel value in mem.CUDAImageAdd[img 1, img 2] gives an ...

CUDAImageMultiply[img, x] multiplies an amount x to each channel value in img.CUDAImageMultiply[mem, x] multiplies an amount x to each channel value in ...

Range::range

AndersonDarlingTest[data] tests whether data is normally distributed using the Anderson\[Dash]Darling test.AndersonDarlingTest[data, dist] tests whether data is distributed ...