How to calculate Mean number and Standard Derivation?

Hello everyone, I have to do a 2D Diffusion Equation model using the Explicit Finite Difference Method.

To calculate the North Boundary Condition I have to use I have to use the Gaussian Boundary Distribution of temperatures of amplitude 100 degrees, which I have done the for loop for the north boundary condition with the formula: T(1,j)= 100*exp(-(j-M)^2/2*SD^2))

clc
close all
clear all

%Lenght of the plate ----------------------------------------------
lx= input ('Enter the desire value for x length:');
ly= input ('Enter the desire value for y length:');

%alpha ------------------------------------------------------------
k=143;                                            %Thermal coductivity (W/m.C)
p=2.8*10^3;                                       %Density (kg/m^3)
c=795;                                            %Specific heat (J/kg.C)
alpha= k/(p*c);                                   %Thermal diffusivity (m^2/s)

%Grid Spacing
h= input('Enter the desire grid spacing:'); 

while rem (lx,h)~=0 || rem (ly,h)~=0
    fprintf ('Incorrect solution \n Please enter a value which results in an integer number:')
    h= input ('Reenter the desire grid spacing:');
end

%Grid Spacing along lx and ly ------------------------------------- 
nc= (lx/h)+1;                                     %Number of columns
nr= (ly/h)+1;                                     %Number of raws 

%Time step --------------------------------------------------------
dt= input ('Enter the desire time step:');       

while dt>= h^2/(4*alpha)
    fprintf('solution is unstable. Please return to dt and choose a smaller value for: %g\n', h^2/(4*alpha))
    dt= input ('Enter the desire time step:');
end

%Fourier Number (fo) ----------------------------------------------
fo= alpha*dt/(h^2);

%Creation of vectors ----------------------------------------------
t=0
T= zeros (nr, nc)+20;

%Norh Boundary conditions ----------------------------------------------
for j= 1:nc
x=(j-1)/(nc-1)
T(1,j)= 100*exp(-(j-M)^2/2*SD^2))
end

However, before de for loop, I would need to calculate M (Mean Number) and SD (Standard Derivation) but I have no idea how to do it. Can someone help me please?

Answer 1

[Superficial]

You don't say what you need the mean or SD of.

But in general, if you want the mean of a vector (a list of numbers), then you can :

vec=[5 5 20] % any numbers you like

vec =

     5     5    20

mean(vec)

ans =

    10

std(vec)
ans =

    8.6603