Marquette University

Department of Mathematics, Statistics and Computer Science

Wim Ruitenburg's Fall 2014 MATH 1300-101

Last updated: November 2014
Comments and suggestions: Email   wimr@mscs.mu.edu

Book, chapter 16 on probability, plus extra notes


Probability from chapter 16

The material in chapter 16 is a bit all over the place. Nevertheless, from the chapter we can learn: Some rules of computing the number of elements of a sample space are: These formulas are particularly useful when the probability space is equiprobable.

Three Doors

This problem is also referred to as the Monty Hall problem. The game host shows us three doors, a red door, a white door, and a blue door. Behind one of these doors there is a big prize. We are asked to pick one of the three doors. Once our choice is final, and the prize is behind the door, we have won. Obviously, our chance of winning is one-third, or 1/3. What happens with our chances when the game show host adapts the rules a bit? Suppose we have picked a door, say the red door. Then the game host opens another door, say the white door, and reveals that there is no prize behind the white door. Now we are offered the options of sticking with the red door, or switch to the blue door. Should we switch, or should we stay? What are our chances for the red door, what for the blue door? Let us change the problem in a seemingly irrelevant way as follows. As before, we are asked to pick one of the three doors. Once our choice is final, and the prize is behind the door, we have won. Obviously, our chance of winning is 1/3. Suppose we have picked the red door. Then a storm blows through the hall, and one of the doors is randomly blown open. Suppose that the white door blew open. Behind it there is no prize. Now we are offered the options of sticking with the red door, or switch to the blue door. Should we switch, or should we stay?

Spinning Wheels

Problems 37 and 38 on page 511 illustrate some spinning wheels, or spinners. In class we added numerical values to each of the sectors of the wheels. We are interested in finding probabilities and expected values of such spinning wheels with numbers in the sectors. When is the game fair (expected value is 0)? When is the game in our favor, that is, a winning game (expected value is positive)? When is the game in favor of the wheel owner, that is, a losing game (expected value is negative)?

The Best of Three Dice

Suppose we have three fair but unusual dice, as follows. Instead of having six sides with values 1, 2, 3, 4, 5, and 6, their sides are allowed to have other values. We have a red, a white, and a blue one. The red one has numbers 2, 2, 2, 2, 6, and 6 on its six sides. The white one has numbers 1, 1, 5, 5, 5, and 5 on its six sides. The blue one has numbers 3, 3, 3, 3, 3, and 3 on its six sides. When we list the six sides in tables, we have a situation like this:
2
2
2
2
6
6
1
1
5
5
5
5
3
3
3
3
3
3
The following game is played between two players. The first player picks one on the dice. Then the second player picks another. Next, both players throw their dice simultaneously. Whoever throws the higher number, wins. With the three dice above, draws are not possible. Question: Which one of these three dice is best? In the game above, it is good to be the second player. No matter which color die the first player picks, the second player can always pick a die of another color which is better than the first one.

The birthday paradox

During the class we had about 45 people (a bunch were absent!). What are the hidden assumptions about the distribution of birthdays of people?

Winning a Losing Game

Suppose you play a color at roulette. You can pick either black or red. Your chance for doubling your money is 18/38, your chance for losing your money is 20/38.

Example Problem(s)

  1. Recommended problems from Chapter 16 of the book:
    1, 4a
  2. When we roll 3 fair dice, what is the probability that none of the 3 dice shows a 1? (Use the product rule.)
    When we roll 3 fair dice, what is the probability that at least one of the 3 dice shows a 1? (Use the previous result.)
  3. When we toss 4 fair coins, what is the probability that none of the 4 coins shows tails? (Use the product rule.)
    When we toss 4 fair coins, what is the probability that at least one of the 4 coins shows tails? (Use the previous result.)
  4. Recommended problems from Chapter 16 of the book:
    17, 23
  5. Recommended problems from Chapter 16 of the book:
    39
  6. We roll a red, a white, and a blue die in a single throw. All dice are normal and fair ones. What is the probability that the red one comes up even, the white one comes up greater than or equal to 5, and the blue one comes up less than 6 all at the same time?
  7. Suppose that in the Monty Hall problem we have 5 doors named A, B, C, D, and E. Behind one of the doors is the big prize we want. We must guess, and we guess door D. Then the game show hosts does the usual thing by opening 3 doors, in this case doors A, C, and E, and shows that there is no prize behind those 3 doors. What is the probability of the prize being behind door B, and what is the probability for the prize being behind door D?
  8. Consider problem 38 of the book, but now we assign numerical values to the sectors as follows. Red sector, value 6. Green sector, value 0. Blue sector, value -1. White sector, value 3. What is the expected value when playing against this spinning wheel?
  9. In the game of the strange red, white, and blue dice, let us add another one, say an orange die, with numbers 3, 3, 3, 4, 4, 4. Otherwise the rules of the game don't change. Is the first player better off, or has nothing really changed and is the second player still better of? Justify your answer.
  10. Suppose the class had 367 people. What is the probability that some of us have the same birthday?
  11. When you play 1 dollar on a number at roulette, say on number 17 or whatever, your chance of winning is 1 in 38, and you get 36 dollars added. If you lose, your 1 dollar is gone. What is your expected value for this game?