Thread: central limit theorm help

Z1,Z2,.... are identically independently distributed with uniform distribution [-20,10]. How do i use the central limit theorem to estimate the the probability
P(summation (900, i=1) : Zi >= -4470)

My attempt
E(Zi)=-5
Var(Zi)=80
P(summation Zi <= -4470) = P([summation Zi]/900 <= [-4470]/900)
=P(sample Z (900) <= 80)
=P([sample Z (900) + 5]/sqrt(80/900) <= [80+5]/sqrt(80/900))
~=P(Z<=285.1) where Z~Normal(0,1)

Originally Posted by Sneaky

Z1,Z2,.... are identically independently distributed with uniform distribution [-20,10]. How do i use the central limit theorem to estimate the the probability
P(summation (900, i=1) : Zi >= -4470)

My attempt
E(Zi)=-5
Var(Zi)=80
P(summation Zi <= -4470) = P([summation Zi]/900 <= [-4470]/900)
=P(sample Z (900) <= 80)
=P([sample Z (900) + 5]/sqrt(80/900) <= [80+5]/sqrt(80/900))
~=P(Z<=285.1) where Z~Normal(0,1)

The distribution of the sum on iid RVs with mean and variance has distribution (approximatly, by the CLT)

The mean of is and its variance is

CB

so i redid it and now i get

1-P(Z<=0.115)

where Z ~ N(0,1)

Is this right?

Originally Posted by Sneaky

so i redid it and now i get

1-P(Z<=0.115)

where Z ~ N(0,1)

Is this right?

Yes

CB