Um, we are gonna use this phrase for mean squares for variance, so they both mean variance, mean square and variance same thing.

The mean is just the probability and the variance.

That is variance and another term for variance is mean squares because it is the mean of the sum squares.

The mean squares over N is the variance.

The mean is 4, and the variance and the standard deviation are 0.

Variance of mean velocity of particles in the measureRect

Variance of mean mass of particles in the measureRect

In a population with a mean height of 70 inches and a variance of 25, what are the mean and variance of the distribution of heights in centimeters?

And the mean and the variance are computed using these two now familiar formula.

I'm giving you a skeleton program, which has a function update, that takes as an input a mean and a variance for the first distribution and a mean and a variance for the second distribution and outputs the new mean and the new variance of the product of those.

Here I am testing it with a mean of 10 and a variance of 8 and a mean of 13 and a variance of 2, which was one of our examples.

The prior has a mean of mu and a variance of sigma squared.

Variance of mean kinetic energy of particles in the measureRect

Mu is the mean. Sigma squared is called the variance.

And now I have a variance co variance matrix.

That is variance explained and variance that is not explained.

Okay, so sum of squares, mean squares, that gives us variance.

Variance

Variance

Variance

That's the formula of the mean, but now I'm asking what's the variance of the mean.

Now I compute the mean of that new ndata and return it that's my variance.

More variance allowed for more co variance.

Just for the exercise of applying the formula, compute for me the mean and the variance.

position variance

angle variance

velocity variance

angularVelocity variance

acceleration variance

angularAcceleration variance

force variance

torque variance

mass variance

inertia variance

momentum variance

Stiffness variance

Damping variance

Position1 variance

Variance 2

Field variance?

I would like to know what is the variance of the mean, not the sum, but the mean.

So we calculated his average or mean points per game and we calculated his variance and standard deviation.

Now the mean is obviously 50, 0.5100, the variance will be 25, 1000.25.

Now I would like you to do the predict function, which takes our current estimate and its variance and the motion and its uncertainty and computes the new updated prediction, mean, and variance.

Compute for me the mean and the variance using the maximum likelihood estimator I just gave you.