Variance in MATLAB
MATLAB provides a simple function to calculate the variance of a given data, the var() function.
Syntax:
variance = var(<data>, <weight>, …)
Here, the <data> is a vector or array of data, and <weight> is an optional argument used for weighted data.
Let’s see the usage of var with some examples.
Example 1:
Matlab
% MATLAB code for Calculating the % variance of a 1D vector [23:75]. % Creating a vector data = 23:75; % Calculating variance variance = var(data); disp(variance) |
Output:
The calculated variance is 238.50, which can be verified manually.
Calculating variance of weighted data. We use the same vector but, just add another vector which stores the weight of every element in the data.
Example 2:
Matlab
% MATLAB code for creating a vector and weights data = 23:75; w=linspace(3,13,53); %calculating variance variance = var(data,w); disp(variance) |
Output:
This will give, us the weighted variance of the user data and weights.
We can also calculate the variance of a multidimensional vector along a particular dimension (less than the maximum dimension) as follows.
Example 3:
Matlab
% MATLAB code forcreating a vector and weights data = [1 3 -2; 2 3 7; 0 4 2.1]; % w = [0.1, 3, 2.1]; % Calculating variance at all dimensions var(data,0, "all" ) % Calculating variance at 1st dimension var(data,0,1) % Calculating variance at 2nd dimension var(data,0,2) |
Output:
How to Calculate Variance in MATLAB?
Pre-requisites: Calculate Variance
In statistical mathematics, Variance is the measure of dispersion of a given data from its average value. This is a very important quantity in statistics and many other fields like Machine Learning and AI.
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