Theoretical Distribution Flashcards
When Binomial Distribution is followed?
- Trial is independent
- The Number of trials are finite integer
- Random variable X is followed by n and P
f(x) = p(X=x) = Binomial Distribution formula
nCx * p^x * q^n-x , X = 0,1,2,…..n
Important properties of Binomial Distribution
Sum of F(x) = 1
Binomial Distribution is bi parametric distribution - (n,p)
Binomial Distribution may be Uni modal or Bi Modal -
if (n+1)p is not a integer , (n+1) p
If (n+1)p is an integer, (n+1)p -1
Poisson Distribution
Formula
Usage
e value
f(x) = P(x) = e^-m * m^x / X!
e = 2.71828
X = 0,1,2,3 ….. Infinity
Formulas Binomial distribution
- Mean
- Variance
- Addictive Property
Mean = np
SD = npq
If p and q are less than or equal to 1, npq<np
Addictive Property -
X ~ B(n,p)
Y ~ C(n,p)
(X+Y) ~ A (n+n , p+p)
Properties of Poisson Distribution
Mean formula
Variance formula
Modal
- e^-m > 0 , m>0 , f(x) Greater than equal to 0
- uniparametric distribution m , one parametric “m”
- mean = m
- Variance = m
- Integer - m and m-1
- Non Integer - Largest integer in m
Addictive property and
Poisson distribution Application
X ~ P(m1)
Y ~ P(m2)
Z = X+Y ~ P(m1+m2)
Application of Poisson Distribution:
- No of Printing mistakes per page
- No. of radioactive element per minute in fusion process
- no. of Road accidents on a busy road per minute
Normal Distribution
Formula
f(x) = 1/ Variance (Square root 2pi) * e^(y)
y = -(x’-u)^2 / 2 variance ^2
Properties of Normal Distribution
QD ,Mean , MD
- bi parametric , Mew and variance
- Mean=Median=Mode = mew
- Mean deviation = 0.8 * Variance
- First Q = mew - 0.675 Var
- Third Q = mew + 0675 Var
- QD = 0.675 var
- Normal Distribution is symmetrical about Mew = x
its skewness is zero
Two Point of inflexion
Mew - 3Var
Mew + 3 var
99.73% - lies between Mew - 3 Var and Mew + 3 var
X ~ N(Mew , SD)
Y ~ B(Mew , SD2)
X+Y ~ A(Mew + Mew, SD + SD2)
Standard Normal Distribution
Formula
and Properties
f(z) = 1/square root 2pi * e^-Z^2 /2
Mean, Mode, Median = 0
SD = 1, then MD = 0.8 and QD = 0.675
SND is symmetrical
two tails of Standard normal deviation never touch the horizontal axis