Recall that for a random variable

following a Bernoulli distribution

, we have the moment-generating function (MGF)

and also recall that the MGF of a sum of i.i.d. random variables is the product of the MGFs of each distribution:

So for a sum of Bernoulli-distributed i.i.d. random variables

, we have

which is the MGF of the binomial distribution

. (Indeed, the Bernoulli distribution is identical to the binomial distribution when

.)
<span>A = Area
L= Length = 15
W + widith = 10
A = 150
The pool area is
L = 10
w= 5
A= 50
So the area of the perimeter = 100 square meters</span>
What how is this a problem and how are you in middle school
Answer:
0.0016
Step-by-step explanation:
Batting average, p = 0.26
n = 7
x = 6
With p = 0.26 as success rate
1-p is equal to failure rate which is = 0.74
We have to solve this by using the binomial distribution formula.
P(X= x)
= nCx * p^x * (1-p)^(n-x)
P(X = 6)
=7C6 × 0.26^6 ×(1-0.26)^(7-6)
= 7 × 0.0003089 × 0..74¹
= 0.0016
So probability that he has exactly 6 hits in his next 7 bats is equal to 0.0016.