Tutorial

1

Probability mass function. Mean, variance.
   Moment generating function.
   Additivity.
   Estimation of the two parameters n and p.

Animation

p and sample size adjustable.
   Mean, mode, standard deviation. 

Tutorial

1

Basic properties of the geometric distribution.
   Geometric r.v. as discretized exponential r.v..

Animation

p and sample size adjustable.
   Mean, mode, standard deviation.

Tutorials

1

Basic properties of the hypergeometric distribution :
       *Mean.
       * Variance.

2

Distribution of two binomial r.v. conditionally to their sum
   is hypergeometric.

Animations

All parameters are adjustable
.   Progressive build-up of the histogram.

.Distribution of two binomial r.v. conditionally to their sum
    is hypergeometric.
    The two binomials are adjustable. Sum is adjustable.
 .   Progressive build-up of the histogram.

Tutorial

1

Basic properties of the multinomial distribution.
   Multinomial coefficient (2 demonstrations).

Tutorial

2

Covariance of two modalities:
       * Direct calculation.
       * By auxiliary Bernoulli variables.

Tutorial

1

Basic properties of the negative binomial distribution.

Animation

Probability p is adjustable.
.  Progressive build-up of the histogram.

Tutorial

1

Basic properties of the Poisson distribution.

2

Additivity property of Poisson random variables.
   Splitting a Poisson variable.
   Poisson variables conditionally to their sum.

Animation

Parameter l is adjustable.
.  Comparison with binomial (n or p adjustable)