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Chapter 6. Probability and Simulation: The Study of Randomness. 6.1 Objectives. Students will be able to: Define Simulation. List the five steps involved in a simulation. Explain what is meant by independent trials. Use a table of random digits to carry out a simulation. - PowerPoint PPT Presentation
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Chapter 6 Probability and Simulation: The Study of Randomness
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Page 1: Chapter 6

Chapter 6

Probability and Simulation:

The Study of Randomness

Page 2: Chapter 6

6.1 Objectives

Students will be able to: Define Simulation. List the five steps involved in a simulation. Explain what is meant by independent trials. Use a table of random digits to carry out a

simulation. Given a probability problem, conduct a simulation

in order to estimate the probability desired. Use a calculator or a computer to conduct a

simulation of a probability problem.

Page 3: Chapter 6

6.1 Simulation

The imitation of chance behavior, based on a model that accurately reflects the phenomenon under consideration, is called simulation.

Page 4: Chapter 6

Simulation Steps

Step 1: State the problem or describe the random phenomenon Toss a coin 10 times. What is the likelihood of a

run of at least 3 consecutive heads or 3 consecutive tails?

Step 2: State the assumptions. There are two: A head or tail is equally likely to occur on each

toss. Tosses are independent of each other (that is,

what happens on one toss will not influence the next toss)

Page 5: Chapter 6

Simulation Steps

Step 3: Assign digits to represent outcomes. One digit simulates one toss of the coin. Odd digits represent heads; even digits

represents tails.

Step 4: Simulate many repetitions. We will complete 25 repetitions for this simulation.

Page 6: Chapter 6

Simulation Steps

Step 5: State your conclusions. We estimate the probability of a run of size 3 by

the proportion

Page 7: Chapter 6

Assigning Digits

Choose a person at random from a group of which 70% are employed. 0, 1, 2, 3, 4, 5, 6 = employed

7, 8, 9 not employed 00, 01, …, 69 employed

70, 71,…, 99 not employed

Choose a person at random from a group of which 73% are employed. 00, 01, …, 72 employed

73, 74, …, 99 not employed

Page 8: Chapter 6

Assigning Digits

Choose a person at random from a group of which 50% are employed, 20% are unemployed, and 30% are not in the labor force. 0, 1, 2, 3, 4 = employed

5, 6 unemployed

7, 8, 9 not in the labor force

0,1 = unemployed

2, 3, 4 = not in the labor force

5, 6, 7, 8, 9, = employed

Page 9: Chapter 6

Example

Page 397 #6.1 Establishing Correspondence State how you would use the following aids to

establish a correspondence in a simulation that involves a 75% chance: A coin

A six-sided dice

A random digit table

A standard deck of playing cards

Page 10: Chapter 6

Example

Page 404 #6.15 The birthday problem Use your calculator and a simulation method to

determine the chances of at least 2 students with the same birthday in a class of 23 unrelated students. Determine the chances of at least 2 people having the same birthday in a room of 41 people. What assumptions are you making in your simulations?

Page 11: Chapter 6

Types of Simulations

Situations in which our interest is in the number of successes out of a fixed number of trials (assuming equal probabilities and independence from trial to trial) are often solved using the binomial distribution.

Situations in which our interest is in how many trials it takes for an event to occur (again assuming equal probabilities and independence from trial to trial) are often solved using the geometric distribution.

Page 12: Chapter 6

6.2 Objectives

Students will be able to Explain how the behavior of a chance event differs in the short

and long run. Explain what is meant by a random phenomenon. Explain what it means to say that the idea of probability is

empirical. Define probability in terms of relative frequency. Define sample space. Define event. Explain what is meant by probability model. Construct a tree diagram. Use the multiplication principle to determine the number of

outcomes in a sample space. Explain what is meant by sampling with replacement and

sampling without replacement.

Page 13: Chapter 6

6.2 Objectives

List the four rules that must be true for any assignment of probabilities.

Explain what is meant by {A U B} and {A ∩ B}. Explain what is meant by each of the regions in a Venn diagram Give an example of two events A and B where A ∩ B = Ø. Use a Venn diagram to illustrate the intersection of two events A

and B. Compute the probability of an event, given the probabilities of the

outcomes that make up the event. Explain what is meant by equally likely outcomes. Compute the probability of an event in the cases of equally likely

outcomes. Define what it means for two events to be independent. Give the multiplication rule for independent events. Given two events, determine if they are independent.

Page 14: Chapter 6

Randomness and Probability

We call a phenomenon random if individual outcomes are uncertain but there is nonetheless a regular distribution of outcomes in a large number of repetitions.

The probability of any outcome of a random phenomenon is the proportion of times the outcome would occur in a very long series of repetitions. That is, the probability is long-term relative frequency.

Page 15: Chapter 6

Types of Probability

Theoretical probability (Classical)

Empirical probability is based on observations rather than theorizing.

Subjective probability

Page 16: Chapter 6

Example

Page 410 #6.21 Pennies Spinning Hold a penny upright on its edge under your

forefinger on a hard surface, then snap it with your forefinger so that it spins for some time before falling. Based on 50 spins, estimate the probability of heads.

Page 17: Chapter 6

Probability Models

The sample space is the set of all possible outcomes.

An event is any outcome or a set of outcomes of a random phenomenon. That is, an event is a subset of the sample space.

A probability model is a mathematical description of a random phenomenon consisting of two parts: A sample space, S and A way of assigning probabilities to events.

Page 18: Chapter 6

Types of models

Discrete models have a countable number of outcomes.

Continuous models correspond to intervals on the number line.

Page 19: Chapter 6

Tree Diagrams

Two dice are rolled. Describe the sample space.

There are 36 possible outcomes.

Start

1st roll

2nd roll

1 2 3 4 5 6

1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6

Page 20: Chapter 6

Two dice are rolled and the sum is noted.

1,11,21,31,41,51,6

2,12,22,32,42,52,6

3,13,23,33,43,53,6

4,14,24,34,44,54,6

5,15,25,35,45,55,6

6,16,26,36,46,56,6

Page 21: Chapter 6

Find the probability the sum is 4.

Find the probability the sum is 11.

Find the probability the sum is 4 or 11.

Page 22: Chapter 6

Multiplication Principle

If you can do one task in n1 ways and a second task in n2 ways, then both tasks can be done in n1 x n2 number of ways.

How many ways can you flip 3 coins?

How many ways can you flip a coin and roll a die?

Page 23: Chapter 6

Replacement

Sampling with replacement

Sampling without replacement

How many 4 digit pin numbers can you make?

How many 4 digit pin numbers can you make if all numbers are distinct?

Page 24: Chapter 6

Example Page 417 #6.35 Rolling Two Dice

In how many ways can you get an even sum?

In how many ways can you get a sum of 5? Of 8?

Describe a pattern you see in the table.

Number of ways

Sum Outcomes

1 2 1, 1

2 3 1,2 2,1

4

5

6

7

8

9

10

11

12

Page 25: Chapter 6

Probability Rules

Rule 1: Any probability is a number between

0 and 1. Rule 2: The sum of the probabilities of all possible

outcomes must equal 1. Rule 3: If two events have no outcomes in common,

the probability that one or the other occurs is the sum of their individual probabilities.

Rule 4: The probability that an event will occur is 1 minus the probability that the even does occur.

Page 26: Chapter 6

Venn diagrams

Mutually exclusive (disjoint)

Union (A U B)

Intersect (A ∩ B)

Page 27: Chapter 6

Venn diagrams

Empty Set

Complement

Page 28: Chapter 6

Equally Likely

If a random phenomenon has k possible outcomes that are all equally likely, then each individual outcome has probability 1/k.

Page 29: Chapter 6

Example Page 423 #6.38 Distribution of M&M colors

If you draw an M&M candy at random from a bag of candies, the candy you draw will have one of six colors. The probability of drawing each color depends on the proportion of each color amoung the candies made.

The table below gives the probability of each color for a randomly chosen milk chocolate M&M:

What must be the probability of drawing a blue candy?

Color: Brown Red Yellow Green Orange Blue

Probability:

0.13 0.13 0.14 0.16 0.20 ?

Page 30: Chapter 6

The probabilities for peanut M&M’s are different.

What is the probability that a peanut M&M is blue? What is the probability that a milk chocolate M&M is

red, yellow or orange? What is the probability that a peanut M&M is one of

these colors?

Color: Brown Red Yellow Green Orange Blue

Probability:

0.12 0.12 0.15 0.15 0.23 ?

Page 31: Chapter 6

Multiplication Rule for Independent Events Rule 5: Two events are independent if

knowing that one occurs does not change the probability that the other occurs. If A and B are independent,

P(A and B) = P(A)P(B)

**A and B are independent iff P(A|B) = P(A)

Page 32: Chapter 6

Caution…

The multiplication rule applies only to independent events. You cannot use it if events are not independent!

The addition rule applies only to disjoint events.

Disjoint does not mean independent.

Page 33: Chapter 6

Example

Page 430 #6.46 Defective Chips An automobile manufacturer buys computer

chips from a supplier. The supplier sends a shipment containing 5% defective chips. Each chip chosen from the shipment has probability 0.05 of being defective, and each automobile uses 12 chips selected independently. What is the probability that all 12 chips in a car will work properly?

Page 34: Chapter 6

Example Page 430 #6.48 College Student Demographics

Choose a random college student at least 15 years of age. We are interested in the events

A = {The person chosen is male}

B = {The person chosen is 25 years or older}

Government data recorded in Table 4.5 (page 292) allow us to assign probabilities to these events.

Explain why P(A) = 0.44 Find P(B) Find the probability that the person chosen is a male at

least 25 years old, P(A and B). Are these events A and B independent?

Page 35: Chapter 6

Example Page 430 #6.51 Telephone Success

Most sample surveys use random digit dialing equipment to call residential telephone numbers at random. The telephone polling firm Zogby International reports that the probability that a call reaches a live person is 0.2. Calls are independent. A polling firm places 5 calls. What is the probability

that none of them reaches a person? When calls are made to New York City, the

probability of reaching a person is 0.08. What is the probability that none of 5 calls made to New York City reaches a person?

Page 36: Chapter 6

Example Page 432 #6.53 Student Survey

Choose a student at random from a large statistics class. Give a reasonable sample space S for answers to each of the following questions. (In some cases you may have the freedom to specify S.) Are you right or left handed? What is your height in centimeters? (1 inch = 2.54 cm) How much money in coins (not bills) are you carrying? How many minutes did you study last night?

Page 37: Chapter 6

Example Page 434 #6.62 Roulette

A roulette wheel has 38 slots, numbers 0, 00, and 1 to 36. The slots 0 and 00 are colored green, 18 of the others are red, and 18 are black. The dealer spins the wheel and at the same time rolls a small ball along the wheel in the opposite direction. The wheel is carefully balanced so that the ball is equally likely to land in any slot when the wheel slows. Gamblers can bet various combinations of numbers and colors. What is the probability that the ball will land in any one

slot? If you bet on “red”, you win if the ball lands in a red slot.

What is the probability of winning? The slot numbers are laid out on a board on which

gamblers place their bets. One column of numbers on the board contains multiples of 3, that is 3, 6, 9, …, 36. You place a ”column bet” that wins if any of these numbers comes up. What is your probability of winning?

Page 38: Chapter 6

6.3 Objectives

Students will be able to State the Addition Rule for disjoint events. State the general addition rule for union of two sets. Given two events A and B, compute P(A U B). Define what is meant by a joint event and joint probability. Given two events, compute their joint probability. Explain what is meant by the conditional probability P(A|B). State the general multiplication rule to define P(B|A). Explain what is meant by Bayes’s rule. Define independent events in terms of a conditional

probability.

Page 39: Chapter 6

Union

The Union of any collection of events is the event that at least one of the collection occurs.

Page 40: Chapter 6

Addition Rule for Disjoint Sets If events A, B, and C are disjoint, then

P(A or B or C) = P(A) + P(B) + P(C)

Page 41: Chapter 6

General Addition Rule for Unions of Two Events P(A or B) = P(A) + P(B) – P(A and B)

Page 42: Chapter 6

Example

Page 441 #6.70 Tastes in Music I Musical styles other than rock and pop are

becoming more popular. A survey of college students finds that 40% like country music, 30% like gospel music, and 10% like both. Make a Venn diagram with these results. What percent of college students like country but

not gospel? What percent like neither country nor gospel?

Page 43: Chapter 6

Conditional Probability

P(A|B) “probability of A, given B”

Page 44: Chapter 6

General Multiplication Rule

The joint probability that events A and B will both happen can be found by

P(A and B) = P(A) x P(B|A)

Here P(B|A) is the conditional probability that B occurs, given the information that A occurs.

Page 45: Chapter 6

Conditional Probability

When P(A) > 0, the conditional probability of B, given A, is

`P(B|A) = P(A and B)

P(A)

Page 46: Chapter 6

Example

Page 446 #6.72 Pay at the Pump At a self-service gas station, 40% of the

customers pump regular gas, 35% pump midgrade, and 25% pump premium gas. Of those who pump regular, 30% pay at least $20. Of those who pump midgrade, 50% pay at least $20. And of those who pump premium, 60% pay at least $20.

What is the probability that the next customer pays at least $20?

Page 47: Chapter 6

Example

Page 447 #6.76 The probability of a flush A poker player holds a flush when all 5 cards in

the hand belong to the same suit. We will find the probability of a flush when all the cards are dealt. Remember that a deck contains 52 cards,13 of each suit, and that when the deck is well shuffled, each card dealt is equally likely to be any of those that remain in the deck. We will concentrate on spades, what is the probability

that the first card dealt is a spade? What is the conditional probability that the second card is a spade, given that the first is a spade?

Page 48: Chapter 6

Continue to count the remaining cards to find the conditional probabilities of a spade on the third, fourth, and fifth card, given in each case that all previous cards are spades.

The probability of being dealt 5 spades is the product of the five probabilities that you have found. Why? What is this probability?

The probability of being dealt 5 hearts or 5 diamonds or 5 clubs is the same as the probability of being dealt 5 spades. What is the probability of being dealt a flush?

Page 49: Chapter 6

Intersection

The intersection of any collection of events is the probability that all of the events occur.

Page 50: Chapter 6

Example

Page 448 Example 6.30

Page 51: Chapter 6

Independent Events

Two events A and B that both have positive probability are independent if

P(B|A) = P(B)


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