################BINOMIALE######
#P(X<=6),n=10,pi=0.2
F6<-pbinom(6,10,0.2)
#P(X<3<=6)
F36sx<-pbinom(6,10,0.2)-pbinom(3,10,0.2)
#P(X<=3<=6)
F36c<-pbinom(6,10,0.2)-pbinom(2,10,0.2)
#P(X<=3<6)
F36sx<-pbinom(5,10,0.2)-pbinom(2,10,0.2)
#P(X=6)
#pbinomfun di ip qbimom funz di ptob
p6<-pbinom(6,10,0.2)-pbinom(5,10,0.2)
p6<-dbinom(6,10,0.2)
################################percentili
mediana<-qbinom(0.5,10,0.2)
##########POISSON#########################################
F6<-ppois(6,5)
F64sx<-ppois(6,5)-ppois(4,5)
F64c<-ppois(6,5)-ppois(3,5)
p6<-dpois(6,5)
#P(X>6)
S6<-1-ppois(6,5)

#####lambda=1 tempo attesa 5 evento <=2################
POIS<-1-ppois(4,2) #usopisson
FGAM<-pgamma(2,5,1) #uso gamma



#############NORMALE#################################
FN<-pnorm(1.96,0,1)
mu<-10
sigma<-2
x<-12
FN2<-pnorm(12,10,2)
FN2bis<-pnorm((12-10)/2,0,1)
fpos<-1-pnorm(2,0,1)
fneg<-pnorm(-2,0,1)
#p(X<12,X>8) mu 10 sigma 2
Fint<-pnorm(12,10,2)-
    pnorm(8,10,2)
Fintbis<-pnorm((12-10)/2,0,1)-
    pnorm((8-10)/2,0,1)
#percentili
z_0.99<-qnorm(0.99,0,1)
x_0.99<-qnorm(0.99,5,2)

xx_0.99<-5+2*z_0.99



#######t student



#P(x<=1)
p<-pt(1,12)
p
q_0.99<-qt(0.99,12)
q_0.99
###chi quadrato

#P(X<=10)
p<-pchisq(10,12)
p

q_0.99<-qchisq(0.99,12)
q_0.99