Unit 4: Review

  1. A new clothing store advertises that during its Grand Opening every customer that enters the store can throw a bouncy rubber cube onto a table that has squares labeled with discount amounts. The table is divided into ten regions. Five regions award a 10% discount, two regions award a 20% discount, two regions award a 30% discount, and the remaining region awards a 50% discount.
  1. What is the probability that a customer gets more than a 20% discount?
  2. What is the probability that a customer gets less than a 20% discount?
  3. What is the probability that the first two customers both get a 50% discount?
  4. What is the probability that none of the first three customers gets more than a 30% discount?
  5. What is the probability that the first customer to win a 30% discount is the sixth customer that enters the store?
  6. What is the probability that there is at least one customer to win a 50% discount among the first five customers that enter the store?
  7. As you enter the store you watch four people in front of you all win 50% discounts. The store manager tells you how lucky you are to be throwing the cube while it is on a hot streak, but a friend with you says you’re unlucky because the streak can’t continue. Comment on their statements.
  1. According to the American Pet Products Manufacturers Association (APPMA) 2003-2004 National Pet Owners Survey, 39% of U.S. households own at least one dog and 34% of U.S. households own at least one cat. Assume 60% of U.S. households own a cat or a dog.
  1. Draw the Venn Diagram
  2. What is the probability that a randomly selected U.S. household owns neither a cat nor a dog?
  3. What is the probability that a randomly selected U.S. household owns both a cat and a dog?
  4. What is the probability that a randomly selected U.S. household owns a cat if the household has a dog?
  5. Is having a dog or a cat mutually exclusive? Explain.
  6. Is having a dog or a cat independent?
  1. If P(A) = 0.65 and P(B) = 0.23 and P(A∩B) = 0.15, find the following:
  2. P(A U B) =
  3. P(B|A) =
  4. Are A and B disjoint events? Why or why not?
  5. Are A and B independent? Why or why not?
  1. If P(D) = 0.37, P(C) = 0.41 and D and C are disjoint, what is the probability of D or C?
  1. If P(K)= 0.71, P(R)= 0.23 and K and R are independent, what is the probability of K and R?
  1. If P(F) = 0.33 and P(H) = 0.28 and P(H|F) = 0.13, find the following:
  2. P(F and H) =
  3. P(F or H) =
  1. If P(A) = 0.25, P(AB)=0.78, and P(AB) = 0.12, find P(B).
  1. On a certain day, there is a 37% chance for rain. The probability of John remembering to bring an umbrella to work and it raining is 15%. What is the probability that John remembers to bring an umbrellagiven thatit rains?
  1. In a History class, 50% of the students are males. The probability of a student being a male and a junior is 20%. What is the probability that a student selected at random is a junior given that the student is a male?
  1. A survey of an introductory statistics class in Autumn 2003 asked students whether or not they ate breakfast the morning of the survey. Results are as follows:

Breakfast
Yes / No
Sex / Male / 66 / 66
Female / 125 / 74
  1. What is the probability that a randomly selected student is female?
  2. What is the probability that a randomly selected student ate breakfast?
  3. What is the probability that a randomly selected student is a female that ate breakfast?
  4. What is the probability that a randomly selected female ate breakfast?
  5. What is the probability that a student who ate breakfast is female?
  6. Does it appear that whether or not a student ate breakfast is independent of the student’s sex? Explain.
  1. A manufacturing firm orders computer chips from three different companies: 10% from Company A; 20% from Company B; and 70% from Company C. Some of the computer chips that are ordered are defective: 4% of chips from Company A are defective; 2% of chips from Company B are defective; and 0.5% of chips from Company C are defective. A worker at the manufacturing firm discovers that a randomly selected computer chip is defective. What is the probability that the computer chip came from Company B?
  1. An industrial psychologist administered a personality inventory test for passive-aggressive traits to 150 employees. Individuals were given a score from 1 to 5, where 1 was extremely passive and 5 extremely aggressive. A score of 3 indicated neither trait. X is the score.
  2. Find the missing probability from the following probability distribution

X = score / 1 / 2 / 3 / 4 / 5
P(X = x) / 0.16 / 0.22 / 0.20 / 0.14
  1. P(X ≤ 3) =
  2. P(1< X ≤4) =
  3. Find the mean and standard deviation.
  1. At a raffle, 1500 tickets are sold at $2 each for four prizes of $500, $250, $150, and $75. Assume all 4 prizes are drawn at the same time (so there is no change in probability between selections of the prizes), and assume all 1500 tickets have an equal chance of being selected.
  1. Create the probability model.
  2. What is the expected value for one play?
  3. Find the standard deviation for one play.
  4. Find the expected value and standard deviation for 3 plays.
  1. The distribution of SAT scores for college-bound male seniors has mean of 1532 and a standard deviation of 312. The distribution of SAT scores for college-bound female seniors has a mean of 1506 and a standard deviation of 304. One male and one female are randomly selected. Assume their scores are independent.
  1. If their scores are added together what is the new mean and standard deviation?
  2. What is the mean and standard deviation of the differences of their scores?
  3. Assuming the difference in the scores is normally distributed, what is the probability that a randomly selected female scored higher than a male on the SAT?

Mean / SD
X / 12 / 5
Y / 18 / 8
  1. Given independent random variables with means and standard deviations as shown, find the mean and standard deviation of each of these variables:

a. -2Xb. 4Y – 7

c. X + Yd. X – Y

e. X1 + X2f. 2X – 4Y

16. The probability distribution below represents (X) the length of long distance calls in minutes.

X / 5 / 10 / 15 / 20 / 25
P(X) / .1 / .2 / .3 / .3 / .1

a. What is the expected length of a long distance call? What is the standard deviation?

b. Suppose that there is an initial connection charge of $.60 and an additional charge of $.015 for each minute. What is the expected cost and standard deviation of the cost of a long distance call?

c. The expected cost of sending a text message is $.20 with a standard deviation of $.10. What is the mean and standard deviation for the cost of making a long distance call and sending a text message?

d. Which costs more, the call or the text? How much more? With what standard deviation?

  1. Suppose 40% of the drivers have jumper cables. You have driven to a large university campus but left your lights on. Now your car has a dead battery and you don’t have jumper cables.
  2. What is the probability that you would need to ask 7 people before finding someone with jumper cables?
  3. What is the probability that you would find someone with jumper cables within the first 5 that you asked?
  4. How many people would you expect to need to ask before you found someone to jump your car?
  5. What is the probability that among 8 drivers 3 would have jumper cables?
  6. What is the probability that among 6 drivers at least 4 would have jumper cables?
  7. What is the probability that among 10 drivers, more than half would have jumper cables?
  8. How many drivers would you expect to have jumper cables if there were 12 in the parking lot?
  9. After never having found someone with jumper cables, and calling you dad for help, you wonder if it isn’t true that 40% of the students of the university have jumper cables. You decide to randomly sample 80 drivers.
  10. Is the normal approximation to the binomial appropriate here?
  11. Write the appropriate model below
  12. Using the normal model, what is the probability that 30 or less have jumper cables?
  13. Using the normal model, what is the probability that between 42 and 61 have jumper cables?
  1. Will Fumble is a receiver for the WHS football team whose consistently catches passes thrown to him 15% of the time.

a. What is the probability that he catches 2 out of 6 passes?

b. What is the probability that he catches at least 3 of 8 passes thrown to him?

c. What is the probability that the first pass he catches is on his 4th attempt?

d. What is the probability that his first catch is on his 5th or 6th attempt?

e. What is the probability that he catches less than 2 out of 10 passes?

f. How many passes out of 12 should he expect to catch? With what standard deviation?

g. What is the expected number of pass attempts before the first pass is caught?

h. If he has 25 passes thrown to him, what is the probability that he catches between 9 and 14 of them?

i. Throughout the season, he has a total of 70 pass attempts thrown to him.

  1. Would the normal model be appropriate?
  2. If so, what is the normal model?
  3. Using this normal model, what is the probability that he will catch 20 of those 70 pass attempts?
  4. Using this normal model, what is the probability that he will catch between 11 and 29 passes?