- Suppose we roll a fair six-sided die 4 times. What is the
probability of getting exactly 2 sixes? Hint: Let X be the number of
sixes obtained in the 3 rolls. Then X has a binomial distribution with n
= 4 and p = 1/6.
dbinom(2, 4, 1/6)
## [1] 0.1157407
- Suppose we were going to flip a biased coin 6 times. The probability
of tossing a head is .8 and a tail .2. What is the probability that
you’ll toss at most 3 heads.
pbinom(3, 6, .8, lower.tail = TRUE)
## [1] 0.09888
- Suppose the probability that a person has blood type B is 0.12. In
order to conduct a study concerning people with blood type B, patients
are sampled independently of one another until 10 are obtained who have
blood type B. Determine the probability that at most 25 patients have to
have their blood type determined. Let Y have a negative binomial
distribution with p = 0.12 and r = 10.
pnbinom(15,10,0.12)
## [1] 0.000362934
- Refer to question #3, find the probability that exactly 15 patients
have to have their blood type determined before the first patient with
type B blood is found.
dgeom(15,0.12)
## [1] 0.01763686
- A deck of cards contains 20 cards: 7 red cards and 14 black cards. 5
cards are drawn randomly without replacement. What is the probability
that exactly 4 red cards are drawn?
dhyper(4,7,14,5)
## [1] 0.02407981
- Suppose the number of people that show up at a bus stop is Poisson
with a mean of 2.5 per hour, and we want to know the probability that at
most 2 people show up in a 4 hour period.
ppois(2, 2.5*4, lower.tail = TRUE)
## [1] 0.002769396
- In a standard normal curve, what is the Z-score value whose area
below it is 0.30?
qnorm(.30)
## [1] -0.5244005
- Find the 97.5th percentile of a normal distribution with mean 5 and
standard deviation 1.5.
qnorm(.975,5,1.5)
## [1] 7.939946
- Suppose you have a normal distribution with mean 1050 and variance
of 1600 and you want to compute the probability that the associated
random variable X lessthan 1100.
pnorm(1100,mean=1050,sd=40,lower.tail=TRUE)
## [1] 0.8943502
- Provide descriptions of two probability distributions in Unit
3.