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Warm-Up

Warm-Up. 1. What is Benford’s Law? What two numbers do all probabilities fall between? What does equally likely outcomes mean? What is the formula for equally likely outcomes? What distribution does Benford’s Law fall under? What distribution does equally likely outcomes follow?.

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Warm-Up

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  1. Warm-Up 1. What is Benford’s Law? • What two numbers do all probabilities fall between? • What does equally likely outcomes mean? • What is the formula for equally likely outcomes? • What distribution does Benford’s Law fall under? • What distribution does equally likely outcomes follow?

  2. Probability: The Mathematics of Chance The Mean and Standard Deviation of a Probability Model • Mean of a Continuous Probability Model • Suppose the area under a density curve was cut out of solid material. The mean is the point at which the shape would balance. • Law of Large Numbers • As a random phenomenon is repeated a large number of times: • The proportion of trials on which each outcome occurs gets closer and closer to the probability of that outcome, and • The mean¯ of the observed values gets closer and closer to μ. (This is true for trials with numerical outcomes and a finite mean μ.) x 2

  3. Experimental Probability • Observing the results of an experiment • An event which has a 0% chance of happening (i.e. impossible) is assigned a probability of 0. • An event which has a 100% chance of happening (i.e. is certain) is assigned a probability of 1. • All other events can then be assigned a probability between 0 and 1.

  4. Experimental Probability Terminology • Number of Trials – the total number of times the experiment is repeated. • The outcomes – the different results possible for one trial of the experiment. • Frequency – the number of times that a particular outcome is observed. • Relative Frequency – the frequency of an outcome expressed as a fraction or percentage of the total number of trials. • **experimental probability = relative frequency**

  5. Sample Space • The set of all possible outcomes of an experiment • Examples: • Tossing a coin • Rolling a die

  6. Example • We roll two dice and record the up-faces in order (first die, second die) • What is the sample space S? • What is the event A: “ roll a 5”?

  7. Probability Model • Example: Rolling two dice • We roll two dice and record the up-faces in order (first die, second die) • All possible outcomes • (1,1) (1,2) (1,3) (1,4) (1,5) (1,6) • (2,1) (2,2) (2,3) (2,4) (2,5) (2,6) • (3,1) (3,2) (3,3) (3,4) (3,5) (3,6) • (4,1) (4,2) (4,3) (4,4) (4,5) (4,6) • (5,1) (5,2) (5,3) (5,4) (5,5) (5,6) • (6,1) (6,2) (6,3) (6,4) (6,5) (6,6) • “Roll a 5” : {(1,4) (2,3) (3,2) (4,1)}

  8. Probability Models • Give me the sample space for: Flipping two coins.

  9. Experimental Probability Examples Coin Tossing & Dice Rolling Coin Toss Dice

  10. 2-D Grids: • Illustrate the possible outcomes when 2 coins are tossed. • Illustrate the possible outcomes for the sum of 2 dice being rolled. 2-D Grid

  11. 2-D Grids: 3. Illustrate the possible outcomes when tossing a coin and rolling a die.

  12. Tree Diagrams Illustrate the possible outcomes when • tossing 2 coins • drawing 2 marbles from a bag containing red, green and yellow marbles Tree Diagrams

  13. Theoretical Probability • For fair spinners, coins or die (where a particular outcome is not weighted) the outcomes are considered to have an equal likelihood. • For a fair dice, the likelihood of rolling a 3 is the same as rolling a 5… both 1 out of 6 • This is a mathematical (or theoretical) probability and is based on what we expect to occur. • A measure of the chance of that event occurring in any trial of the experiment

  14. Warm-Up • Have your homework out on your desk. • Create a tree diagram for the following. • Flipping two coins • Pulling a marble out of a bag full of blue, green and yellow marbles. • How many outcomes total? • What is the probability of pulling a blue marble out of the bag? • What is the probability of flipping heads in the scenario?

  15. Homework Answers

  16. Theoretical Probability Examples • A ticket is randomly selected from a basket containing 3 green, 4 yellow and 5 blue tickets. Determine the probability of getting: • A green ticket • A green or yellow ticket • An orange ticket • A green, yellow or blue ticket

  17. Complementary Events • An ordinary 6-sided die is rolled once. Determine the chance of: • Getting a 6 • Not getting a 6 • Getting a 1 or 2 • Not getting a 1 or 2

  18. Warm-Up • Have your homework out on your desk.

  19. Homework Check

  20. More Grids to Find Probabilities • Use a two-dimensional grid to illustrate the sample space for tossing a coin and rolling a die simultaneously. From this grid determine the probability of: • Tossing a head • Getting a tail and a 5 • Getting tail or a 5

  21. More Grids to Find Probabilities (cont.) • 2 circular spinners, each with 1 – 10 on their edges are twirled simultaneously. Draw a 2D grid of the possible outcomes and use your grid to determine the probability of getting • A 3 with each spinner • A 3 and a 1 • An even result for each spinner Spinner

  22. Warm-Up Compound Events • Create a 2-D grid for the following situation. • A coin is tossed and at the same time, a die is rolled. The result for the coin will be outcome A and the die, outcome B.

  23. Homework Check

  24. 1. A coin is tossed three times. Find the probability that the result is at least two heads. • 1/2 B. 1/3 • C. 3/8 D. None of these

  25. 2. A card is drawn from a standard deck of 52 cards. Then, a second card is drawn from the deck (without replacing the first one). Find the probability that a red card is selected first and a spade is selected second. • 1/3 B. 1/8 C. 13/102 D. None of these

  26. 3. From an urn containing 16 cubes of which 5 are red, 5 are white, and 6 are black, a cube is drawn at random. Find the probability that the cube is red or black. • 11/16 B. 9/16 C. 15/128 D. 5/16

  27. 4. Two events that have nothing in common are called: A. inconsistent B. mutually exclusive C. complements D. Both A and B

  28. 5. A bag contains 5 white balls and 4 red balls. Two balls are selected in such a way that the first ball drawn is not replaced before the next ball is drawn. Find the probability of selecting exactly one white ball. • 12/72 B. 20/72 C. 5/9 D. 4/5

  29. 6. A and B are two events such that p(A) = 0.2 and p(B) = 0.4. If , find . • 0.45 B. 0.6 • C. 0.85 D. None of these

  30. Warm-Up • Create a tree diagram. When you go to a restaurant you have a choice for three course meals your 4 salad choices, 6 entrees, and 5 dessert choices. • How many possible outcomes are there?

  31. Independent Events • Events where the occurrence of one of the events does not affect the occurrence of the other event. • In general, if A and B are independent events, then • P(A and B) = P(A) x P(B) • Ex: a coin and a die are tossed simultaneously. Determine the probability of getting a head and a 3 without using a grid.

  32. Using Tree Diagrams

  33. Examples:

  34. Examples (cont.): • Carson is not having much luck lately. His car will only start 80% of the time and his moped will only start 60% of the time. • Draw a tree diagram to illustrate the situation. • 1st set of branches for the car, 2nd set of branches for the moped • Use the diagram to determine the chance that • Both will start • He has to take his car. • He has to take the bus.

  35. Dependent Events • Think About It: A hat contains 5 red and 3 blue tickets. One ticket is randomly chosen and thrown out. A second ticket is randomly selected. What is the chance that it is red? • Not independent; the occurrence of one of the events affects the occurrence of the other event. • If A and B are dependent events then P(A then B) = P(A) x P(B given that A has occurred)

  36. Examples: • A box contains 4 red and 2 yellow tickets. Two tickets are randomly selected one by one from the box, without replacement. Find the probability that: • Both are red • The first is red and the second is yellow

  37. Examples (cont.): • A hat contains tickets with numbers 1 – 20 printed on them. If 3 tickets were drawn from the hat without replacement, determine the probability that all are prime numbers.

  38. Examples (cont.): • A box contains 3 red, 2 blue and 1 yellow marble. Draw a tree diagram to represent drawing 2 marbles. • With replacement Without replacement • Find the probability of getting two different colors: • If replacement occurs • If replacement does not occur

  39. Examples (cont.): • A bag contains 5 red and 3 blue marbles. Two marbles are drawn simultaneously from the bad. Determine the probability that at least one is red.

  40. Z Is it a fair game? • Questions will be put up on the board • For each, you have to decide if the game is: • Fair • Not Fair • Once you decide on your answer, write it on your mini-whiteboard • Only show the you answer when asked

  41. Is it a fair game? Z • Three people have boards like the one shown below. You throw a coin onto a board, if it lands on a shaded square you win • (assume the coin lands exactly in a square)

  42. Is it a fair game? Z A marble is picked from the container by the teacher If its red the girls get a point, if its blue the boys get a point

  43. Is it a fair game? Z Nine cards numbers 1 to 9 are used for a game A card is drawn at random If a multiple of 3 is drawn team A gets a point If a square number is drawn team B gets a point If any other number is drawn team C gets a point 1 2 3 4 5 6 7 8 9

  44. Is it a fair game? Z A spinner has 5 equal sectors numbers 1 to 5, it is spun many times If the spinner stops on an even number team A gets 3 points If the spinner stops on an odd number team B gets 2 points 5 1 4 2 3

  45. Warm Up • Get your homework out. • A box contains 4 red marbles, 5 blue marbles and 1 green marble. We select 2 marbles without replacement. Determine the probability of getting: • At least 1 red marble • One green and one blue marble

  46. Sets & Venn Diagrams • A Venn diagram consists of a rectangle which represents the sample space and at least 1 circle within it representing particular events.

  47. Examples • The Venn diagram represents a sample space of students. The event E, shows all those that have blue eyes. Determine the probability that a student • Has blue eyes

  48. Examples (cont.) • Draw a Venn diagram and shade the regions to represent the following: • 1. In A but not in B 2. Neither in A nor B

  49. denotes the union of the sets A and B. • A or B or both A and B. • denotes the intersection of sets A and B. • All elements common to both sets. • Disjoint sets do not have elements in common. So • A and B are said to be mutually exclusive.

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