Normal distribution

The mean is represented by a triangle than can be seen as a point of equilibrium. By dragging it we can modify the mean. We can get the same effect moving the point at the top of the curve.

Dragging the other point on the curve (which is one of the two inflexion points of the curve) we modify the standard deviation.

We can see the accumulative distribution function and how it change by modifiyng the mean (simple translation) and the standard deviation (reflecting greater or lesser dispersion of the variable).

The gray dots control the vertical and horizontal scales. By pressing the right button and dragging we can move left and right.

LINKS

	One, two and three standar deviations One important property of normal distributions is that if we consider intervals centered on the mean and a certain extent proportional to the standard deviation, the probability of these intervals is constant regardless of the mean and standard deviation of the normal distribution considered.
	Calculating probabilities in Normal distributions It may be interesting to familiarize ourselves with the probabilities correspondig to different intervals in normal distributions.
	Binomial distribution When modeling a situation where there are n independent trials with a constant probability p of success in each test we use a binomial distribution.
	Normal approximation to Binomial distribution In some cases, a Binomial distribution can be approximated by a Normal distribution with the same mean and variance.
	Poisson distribution Poisson distribution is discrete (like the binomial) because the values that can take the random variable are natural numbers, although in the Poisson distribution all the possible cases are theoretically infinite.
	Student's t-distributions Student's t-distributions were studied by William Gosset(1876-1937) when working with small samples.
	Calculating probabilities in t Student distributions (Spanish)