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Lec 18
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GEM2900 Understanding Uncertainty and Statistical ThinkingNotes for lecture 18
Derivation of binomial probability function:
Recall the notation (n
x
)=
n!
x!(n− x)!
for the number of ways of choosing x objects from n without regard to order.Here i! is the product of integers up to i. Sometimes the notation nCx isalso used.
The binomial probability function is
P (X = x) =
(n
x
)px(1 − p)n−x x = 0, ..., n.
The probability of x successes and n − x failures in a particular order ispx(1 − p)n−x (probability p for each of the x successes, 1 − p for each of then− x failures, and multiply the probabilities because of independence). Weneed to multiply this expression by the number of ways of having x successes(i.e.
(nx
)) to get P (X = x).
Example: n = 3, x = 1. Consider the particular sequence of successes andfailures SFF where the notation means success on the first trial, failure onthe second and third trials. Clearly
P (SFF ) = P (S)P (F )P (F ) = p(1 − p)2
illustrating our rule of “probability of x successes and n − x failures in aparticular order is px(1 − p)n−x”. Now, how many ways can we have onesuccess in three trials? Clearly the success can be on the first trial, or thesecond, or the third. The possibilities are SFF , FSF and FFS. There are(nx
)=
(31
)= 3 possibilities. Multiplying p(1 − p)2 by 3 gives the probability
of one success.
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