Concept understanding — Mean and Variance of Binomial Distribution
For X∼B(n,p), three summary numbers describe the whole distribution without listing every term of the p.m.f.: the mean μ=E(X)=np (the average number of successes over many repetitions of the n-trial experiment), the variance Var(X)=npq (how spread out the successes are around that mean), and the standard deviation SD(X)=σX=npq. These are stated as formulae without proof. They are used two ways: forward, when n and p are known, to compute E(X) and Var(X) directly; and backward, when two of E(X), Var(X), n, p are given and the other two must be recovered - typically by dividing Var(X)=npq by E(X)=np to isolate q=Var(X)/E(X) first (since the n cancels), then p=1−q, and finally n=E(X)/p.
E(X)=5, Var(X)=2.5; find n and p.
✓Final answer
n=10, p=0.5.
q=E(X)Var(X)=52.5=0.5, so p=1−0.5=0.5.
From E(X)=np=5: n=0.55=10.
✓Final answer
n=10, p=0.5.
Divide variance by mean to isolate q (the n cancels out of npq/np), then get p=1-q, then n=mean/p.
Trying to solve the two equations np=5 and npq=2.5 for n and p simultaneously as a system, instead of dividing them first to eliminate n.