Why does this probability density function looks off?

I have a random variable x which has a mean of 10 and a variance of 16. I used the following code to generate the array and the PDF:
x= randn(100,1) * sqrt(16)+10;
mu = 10;
sigma = 4;
pd = makedist('Normal',mu,sigma);
y=pdf(pd,x);
hist(y)
Should i be plotting with something other than hist or is x itself wrong? Thank you.

 Akzeptierte Antwort

the cyclist
the cyclist am 24 Jan. 2017
Bearbeitet: the cyclist am 24 Jan. 2017

The mistake is in using hist. Plot x vs. y instead, because y is the value of the pdf itself.

x= randn(100,1) * sqrt(16)+10;
mu = 10;
sigma = 4;
pd = makedist('Normal',mu,sigma);
y=pdf(pd,x);
figure
plot(x,y,'.')

5 Kommentare

Ok but it doesn't look like the probabilities add to 1?
the cyclist
the cyclist am 24 Jan. 2017
Bearbeitet: the cyclist am 24 Jan. 2017
Remember, it is not the values of pdf(x) that sum to 1. It is dx*pdf(x) that sums to one.
You have not chosen evenly spaced x values, and they are not sorted, so it is just a bit tricky to prove it.
[sorted_x,sortingIndex] = sort(x);
dx = [0; diff(sorted_x)];
probabilitySum = sum(dx.*y(sortingIndex))
This gives 0.9866 in the case I tested, which is about as close as I would expect for N = 100.
Ok cool, but for instance when I try to figure out the probability that x>5 I get an oddly low value of around 7. When I feel like it should be closer to 100. Here's how I coded it:
P=x>5;
Probability_x_greater_than_5=sum(P.*y);
the cyclist
the cyclist am 25 Jan. 2017
Bearbeitet: the cyclist am 25 Jan. 2017

You fell into the same trap of not multiplying by dx. I'm not certain, but you may also failed to account for the fact that your values of y are not ordered. So, I think you may have gotten a more-or-less random answer.

There is no need to choose your x at random. It would be much better to choose an evenly spaced array of x from the beginning, and your whole problem becomes simpler.

Like this ...

mu = 10;
sigma = 4;
dx = 0.01;
x = mu - 5*sigma : dx : mu + 5*sigma;
pd = makedist('Normal',mu,sigma);
y=pdf(pd,x);
figure
plot(x,y)
probability_total = sum(dx*y)
Probability_x_greater_than_5 = sum(dx.*y(x>5))

I got 0.8941 for that probability.

Notice that these are probabilities, so they lie between 0 and 1. If you want them represented as percentages, then divide by 0.01.

Awesome thank you very much that was a good explanation!

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