Thread: Project exploring Gaussian Randome Variable and Gaussian Random Numbers.

Here is a problem.

Generate a histogram of gaussian random numbers drawn from a population with a mean value of 10 and standard deviation of 2. Include a sufficient number of samples and bins such that the resulting histogram approximates the Gausssina densitiy function in appearance.
Plot the theoretical envelope over the histogram to demonstrate the validity of the simulation. The histogram should show number of samples per bin. The abscissa should be labeled as numbers, not bins. DO not normalize the histogram to unity.

Im trying to use matalb or any kidn fo math program for this project, i need all the help i can get, just need help from anyone how to start this on prob matlab..

Originally Posted by mayimbej

Here is a problem.

Generate a histogram of gaussian random numbers drawn from a population with a mean value of then and standard deviation of two. Include a sufficient number of samples and bins such that the resulting histogram approximates the Gausssina densitiy function in appearance.
Plot the theoretical envelope over the histogram to demonstrate the validity of the simulation. The histogram should show number of samples per bin. The abscissa should be labeled as numbers, not bins. DO not normalize the histogram to unity.

Im trying to use matalb or any kidn fo math program for this project, i need all the help i can get, just need help from anyone how to start this on prob matlab..

The following will generate a sample of size N from a normal distribution with
mean mu and SD sigma:

Code:

mu=10;
sigma=2;
N=1000;

sample=mu+sigma*randn(1,N);

RonL

Gaussian formula * 10^6 to get smooth sample and 100 bins, determining the theoretical envelope.

x= (1;00000 1:20) ; and array from 1 -20