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.
For example, if we toss n equal coins and we count heads as success, the probability of getting head can be any value between 0 and 1.
A binomial distribution is characterized by two parameters: n (a natural number) and p a number between 0 and 1.
The mean is n.p and its variance is n.p.(1-p)
In the applet we can change the parameter n.
The mean is represented by a triangle and it can be seen as a point of equilibrium. By dragging we can modify parameter p.
We can show a normal curve that has the same mean and variance as the binomial distribution. This normal curve is close to the binomial and can be used for calculations. You can see why it is recommended, in some cases, to extend the interval for which you want to calculate the probability of the binomial in 0.5 above and below to use the normal distribution to approximate the probability.
The gray points control vertical and horizontal scales. Pressing the right button and dragging you can move left and right.
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