The normal distribution is an assumption of many parametric statistical tests, and is typically associated with a Gaussian distribution, often with mean=0 and standard deviation=1. The "bell curve" is the visual, intuitive model for this distribution.
Given the start and the end of an integer range, how do I calculate a normally distributed random integer between …
c# random range gaussian normal-distributionHow can we plot (in python matplotlib) bivariate Gaussian Distributions , given their centers and covariance matrices as numpy arrays? Let's …
python numpy statistics matplotlib normal-distributionI would like to know if in C++ standard libraries there is any gaussian distribution number generator, or if you …
c++ gaussian normal-distributionI have a set of data, for which I'd like to find an average peak. I've done some testing in …
normal-distributionI have been playing around with the MASS package and can plot the two bivariate normal simply using image and …
r plot normal-distributionI'm trying to use the C++ STD TechnicalReport1 extensions to generate numbers following a normal distribution, but this code (adapted …
c++ tr1 normal-distributionGiven mean and variance of a Gaussian (normal) random variable, I would like to compute its probability density function (PDF). …
python scipy distribution normal-distributionI need to generate random numbers that follow a normal distribution which should lie within the interval of 1000 and 11000 with …
c++ c++11 random normal-distributionI'm trying to fit a multivariate normal distribution to data that I collected, in order to take samples from it. …
matlab distribution probability normal-distribution data-fittingI would like to generate n random numbers e.g., n=200, where the range of possible values is between 2 and 40 …
python numpy random normal-distribution