Function Reference: normcdf

statistics: p = normcdf (x)
statistics: p = normcdf (x, mu)
statistics: p = normcdf (x, mu, sigma)
statistics: p = normcdf (…, "upper")
statistics: [p, plo, pup] = normcdf (x, mu, sigma, pcov)
statistics: [p, plo, pup] = normcdf (x, mu, sigma, pcov, alpha)
statistics: [p, plo, pup] = normcdf (…, "upper")

Normal cumulative distribution function (CDF).

For each element of x, compute the cumulative distribution function (CDF) at x of the normal distribution with mean mu and standard deviation sigma. The size of p is the common size of x, mu and sigma. A scalar input functions as a constant matrix of the same size as the other inputs.

Default values are mu = 0, sigma = 1.

When called with three output arguments, [p, plo, pup] it computes the confidence bounds for p when the input parameters mu and sigma are estimates. In such case, pcov, a 2-by-2 matrix containing the covariance matrix of the estimated parameters, is necessary. Optionally, alpha has a default value of 0.05, and specifies 100 * (1 - alpha)% confidence bounds. plo and pup are arrays of the same size as p containing the lower and upper confidence bounds.

[…] = normcdf (…, "upper") computes the upper tail probability of the normal distribution. This can be used to compute a right-tailed p-value. To compute a two-tailed p-value, use 2 * normcdf (-abs (x), mu, sigma).

See also: norminv, normpdf, normrnd, normfit, normlike, normstat

Source Code: normcdf