Download Chapter 8 - Test Review

Final Review
 On
the Saturday after Christmas, it has been
estimated that about 14.3% of all mall-goers
are there to return or exchange holiday gifts.
25 randomly selected customers are surveyed
regarding their purposes at the mall. What is
the probability that exactly 4 customers are
returning/exchanging holiday gifts? At most
4? At least 4?
 Considering
the same information as the last
problem, What is the probability that the
interviewer will find the someone who is
returning/exchanging holiday gifts on
exactly the 4th interviewed customer?
 Again
with the 14.3% returning or exchanging
holiday gifts and the 25 randomly selected
consumers … What is the mean, variance
and standard deviation of the number of
customers that are returning/exchanging
holiday gifts?
 Again
with the 14.3% returning or exchanging
… What is the mean, variance and
standard deviation of the number of
customers that are typically interviewed
before finding the first one who is
returning/exchanging holiday gifts?
 What
is the probability that the interviewer
will have to interview more than 7 customers
in order to finally find someone that is a
returner/exchanger? (Two approaches)
…
More than 10 customers?
…
No more than 6?
 What
is the shape of a Binomial Distribution
with:



p = 0.5
p < 0.5
p > 0.5
 What
is the shape of a Geometric Distribution
with:



p = 0.5
p < 0.5
p > 0.5
 31.4%
of all women report an irrational fear
of mice. An SRS of 7000 women are
questioned about their phobias. What is the
probability that there will be at least 2267 in
this sample that are afraid of mice? Use a
Normal Approximation approach. Why is it
justified? Could we do this calculation with a
class of 30 girls?
A
fair coin (one for which both the
probability of heads or tails are both 0.5) is
tossed 30 times. The probability that less
than 3/5 of the tosses are heads is:
 Suppose
that we select an SRS of size n = 150
from a large population having proportion p
of successes. Let X be the number of
successes in the sample. For what smallest
value of p would it be safe to assume the
sampling distribution of X is approximately
normal? What if n = 40? What if n = 4000?
 Suppose
that we select an SRS of size n from
a large population having proportion p = .08
of successes. For what smallest value of n
would it be safe to assume the sampling
distribution of X is approximately normal?
What if p = .2? What if p = .9995?