Uniform distribution: every datum in range equally likely.
mean=(start+end)/2 ie. midrange
standard deviation= (end-start)/√12 ≈ (end-start)/3.464
Normal/Gaussian distribution: physical quantity that is the sum of many small independent processes.
Also, distribution of sample averages.
Binomial distribution: #successes/yeses/ones in n tries when probability of a success is p.
standard deviation= √(np(1-p))
n=1 : Bernoulli distribution. p=proportion success
Poisson distribution: λ=expected/average independent #events in an interval.
Probabilities of each k (0-) #occurences/events/arrivals in an interval.
standard deviation= √λ
Χ2 Chi-squared distribution: sum of k squared standard normals
standard deviation= √(2k)
kurtosis: 12/k ?
Lognormal distribution: its log is normally distributed.
μ and σ are mean and standard deviation of that normal distribution.
standard deviation= eμ+σ2/2√(eσ2-1)