eight eight
This is a binomial probability distribution. The number of trials, n, equals 30; and the probability of success is p, which is 0.1. In this problem, you want the probability of at least 5, which is the complement of at most 4. We use the complement because we can subtract from 1 that probability and we will have the solution. The related link has the binomial probability distribution table which is cumulative. Per the table, at n=30, p=0.1 and x = 4; the probability is 0.825. Therefore the probability of at least 5 is 1 - 0.825 or 0.175.
The probability that an event will occur plus the probability that it will not occur equals 1.
Probability equals favorable outcomes divided by total number of outcomes.
The number 1. The area of any probability distribution equals 1.
b is incorrect while c is virtually meaningless.
For a binomial probability distribution, the variance is n*p*q which is 80*.3*.7 = 16.8. The standard deviation is square root of the variance which is 4.099; rounded is 4.1. The mean for a binomial probability distribution is n*p or 80*.3 or 24.
This is a binomial probability distribution. The number of trials, n, equals 30; and the probability of success is p, which is 0.1. In this problem, you want the probability of at least 5, which is the complement of at most 4. We use the complement because we can subtract from 1 that probability and we will have the solution. The related link has the binomial probability distribution table which is cumulative. Per the table, at n=30, p=0.1 and x = 4; the probability is 0.825. Therefore the probability of at least 5 is 1 - 0.825 or 0.175.
a and b both have the probability of 3/4
The probability that an event will occur plus the probability that it will not occur equals 1.
It does not matter.
The probability is 0.664
MTBF (mean time between failure)
Multiply each term of the binomial by the monomial. Be particularly careful with signs: (+ times +) or (- times -) equals plus or Like signs = + (+ times -) or (- times +) equals minus or Unlike signs = -
Probability equals favorable outcomes divided by total number of outcomes.
Impossible
The answer depends on what the distribution is!
The number 1. The area of any probability distribution equals 1.