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Probability & Statistics Symbols

Probability & Statistics Symbols – List of all probability & statistics symbols and signs – meaning and examples.

Symbol Symbol Name Meaning / definition Example
P(A) probability function probability of event A P(A) = 0.5
P(B) probability of events intersection probability that of events A and B P(AB) = 0.5
P(B) probability of events union probability that of events A or B P(AB) = 0.5
P(AB) conditional probability function probability of event A given event B occured P(A | B) = 0.3
f (x) probability density function (pdf) P(a x b) = ∫ f (x) dx
F(x) cumulative distribution function (cdf) F(x) = P( x)
μ population mean mean of population values μ = 10
E(X) expectation value expected value of random variable X E(X) = 10
E(X | Y) conditional expectation expected value of random variable X given Y E(X | Y=2) = 5
var(X) variance variance of random variable X var(X) = 4
σ2 variance variance of population values σ2 = 4
std(X) standard deviation standard deviation of random variable X std(X) = 2
σX standard deviation standard deviation value of random
variable X
σX  = 2 median middle value of random variable x cov(X,Y) covariance covariance of random variables X and Y cov(X,Y) = 4
corr(X,Y) correlation correlation of random variables X and Y corr(X,Y) = 0.6
ρX,Y correlation correlation of random variables X and Y ρX,= 0.6
summation summation – sum of all values in range of series ∑∑ double summation double summation Mo mode value that occurs most frequently in population
MR mid-range MR = (xmax+xmin)/2
Md sample median half the population is below this value
Q1 lower / first quartile 25% of population are below this value
Q2 median / second quartile 50% of population are below this value = median of samples
Q3 upper / third quartile 75% of population are below this value
x sample mean average / arithmetic mean x = (2+5+9) / 3 = 5.333
s2 sample variance population samples variance estimator s 2 = 4
s sample standard deviation population samples standard deviation estimator s = 2
zx standard score zx = (xx) / sx
X ~ distribution of X distribution of random variable X X ~ N(0,3)
N(μ,σ2) normal distribution gaussian distribution X ~ N(0,3)
U(a,b) uniform distribution equal probability in range a,b X ~ U(0,3)
exp(λ) exponential distribution f (x) = λeλx , x≥0
gamma(c, λ) gamma distribution f (x) = λ c xc-1eλx / Γ(c), x≥0
χ 2(k) chi-square distribution f (x) = xk/2-1ex/2 / ( 2k/2 Γ(k/2) )
F (k1, k2) F distribution
Bin(n,p) binomial distribution f (k) = nCpk(1-p)n-k
Poisson(λ) Poisson distribution f (k) = λkeλ / k!
Geom(p) geometric distribution f (k) =  p (1-p) k
HG(N,K,n) hyper-geometric distribution
Bern(p) Bernoulli distribution

साप्ताहिक भविष्यफल अक्टूबर 2019

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