Chapter 4 Probability Theory 4.1 What is Probability?

Slides:



Advertisements
Similar presentations
A Survey of Probability Concepts
Advertisements

A Survey of Probability Concepts
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
Chapter 6 Probability and Simulation
Randomness and Probability
Section 5.1 and 5.2 Probability
COUNTING AND PROBABILITY
How likely something is to happen.
From Randomness to Probability
MAT 103 Probability In this chapter, we will study the topic of probability which is used in many different areas including insurance, science, marketing,
Probability Sample Space Diagrams.
Chapter 3 Probability.
1 1 PRESENTED BY E. G. GASCON Introduction to Probability Section 7.3, 7.4, 7.5.
1 Chapter 6: Probability— The Study of Randomness 6.1The Idea of Probability 6.2Probability Models 6.3General Probability Rules.
Chapter 4 Using Probability and Probability Distributions
Business Statistics: A Decision-Making Approach, 7e © 2008 Prentice-Hall, Inc. Chap 4-1 Business Statistics: A Decision-Making Approach 7 th Edition Chapter.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
Probability Part 2 Disjoint and Independent Events
Chapter 6 Probability.
Probability Chapter 3. § 3.1 Basic Concepts of Probability.
Elementary Probability Theory
Probability and Long- Term Expectations. Goals Understand the concept of probability Grasp the idea of long-term relative frequency as probability Learn.
X of Z: MAJOR LEAGUE BASEBALL ATTENDANCE Rather than solving for z score first, we may be given a percentage, then we find the z score, then we find the.
(13 – 1) The Counting Principle and Permutations Learning targets: To use the fundamental counting principle to count the number of ways an event can happen.
1-1 Copyright © 2015, 2010, 2007 Pearson Education, Inc. Chapter 13, Slide 1 Chapter 13 From Randomness to Probability.
Chapters 14/15 AP Statistics Mrs. Wolfe
Chapters 14 & 15 Probability math2200. Random phenomenon In a random phenomenon we know what could happen, but we don’t know which particular outcome.
PROBABILITY. Counting methods can be used to find the number of possible ways to choose objects with and without regard to order. The Fundamental Counting.
Probability Section 7.1.
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin A Survey of Probability Concepts Chapter 5.
Copyright © 2014 Pearson Education, Inc. All rights reserved Chapter 5 Modeling Variation with Probability.
Rev.F081 STA 2023 Module 4 Probability Concepts. Rev.F082 Learning Objectives Upon completing this module, you should be able to: 1.Compute probabilities.
March 10,  Counting  Fundamental Counting principle  Factorials  Permutations and combinations  Probability  Complementary events  Compound.
Chapter 7 Probability. 7.1 The Nature of Probability.
Copyright © 2010 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
Copyright © 2010 Pearson Education, Inc. Chapter 6 Probability.
WRITE DOWN 5 WAYS IN WHICH YOU SEE/USE PROBABILITY IN EVERY DAY LIFE.
Copyright © 2010 Pearson Education, Inc. Unit 4 Chapter 14 From Randomness to Probability.
From Randomness to Probability Chapter 14. Dealing with Random Phenomena A random phenomenon is a situation in which we know what outcomes could happen,
Probability The Study of Chance! Part 3. In this powerpoint we will continue our study of probability by looking at: In this powerpoint we will continue.
Math 30-2 Probability & Odds. Acceptable Standards (50-79%)  The student can express odds for or odds against as a probability determine the probability.
AP Statistics Notes Chapter 14 and 15.
From Randomness to Probability CHAPTER 14. Randomness A random phenomenon is a situation in which we know what outcomes could happen, but we don’t know.
Probability. What is probability? Probability discusses the likelihood or chance of something happening. For instance, -- the probability of it raining.
+ Chapter 5 Overview 5.1 Introducing Probability 5.2 Combining Events 5.3 Conditional Probability 5.4 Counting Methods 1.
Chapters 14 & 15 Probability math2200. Randomness v.s. chaos Neither of their outcomes can be anticipated with certainty Randomness –In the long run,
Chapter 14 From Randomness to Probability. Dealing with Random Phenomena A random phenomenon: if we know what outcomes could happen, but not which particular.
 Counting  Fundamental Counting principle  Factorials  Permutations and combinations  Probability  Complementary events  Compound events  Independent.
Copyright © 2010 Pearson Education, Inc. Chapter 14 From Randomness to Probability.
Chapter 15 Probability Rules!. The General Addition Rule If A and B are disjoint use: P(A  B) = P(A) + P(B) If A and B are not disjoint, this addition.
Probability. Definitions Probability: The chance of an event occurring. Probability Experiments: A process that leads to well- defined results called.
Chapter 14 Probability Rules!. Do Now: According to the 2010 US Census, 6.7% of the population is aged 10 to 14 years, and 7.1% of the population is aged.
AP Statistics From Randomness to Probability Chapter 14.
Section 5.1 and 5.2 Probability
Aim: What is the multiplication rule?
From Randomness to Probability
Elementary Probability Theory
PROBABILITY Probability Concepts
Probability ·  fraction that tells how likely something is to happen ·   the relative frequency that an event will occur.
From Randomness to Probability
From Randomness to Probability
Chapter 15: Probability Rules!
From Randomness to Probability
From Randomness to Probability
Probability Probability underlies statistical inference - the drawing of conclusions from a sample of data. If samples are drawn at random, their characteristics.
Chapter 3 Probability.
Honors Statistics From Randomness to Probability
The “Complicated” Probabilty Disjoint and Independent Events
From Randomness to Probability
6.1 Sample space, events, probability
Presentation transcript:

Chapter 4 Probability Theory 4.1 What is Probability?

Law of Large Numbers Jacob Bernoulli: “For even the most stupid of men… is convinced that the more observations have been made, the less danger there is of wandering from one’s goal” Law of Averages is what people say when they assume that eventually they will win the lottery. Law of averages compensates for loss. Law of Averages does not exist.

Imagine.. You have a hankering for an egg and cheese on a roll (ketchup, salt, pepper..). It is the first day of open campus for seniors, so during your free period you get in the car and drive down to Neils. You get to the light at the end of Martinsville road and it is red. Are you anxious? Do you worry about getting back in time, on this your first day of open campus? The next day you have the same hankering… and the light is red again – what are the odds??? The following day...you guessed it. Would you then decide to go to O’Bagel? Do you really think that the probability of hitting the red light is 100% Probably not…

Probability Probability is the long run relative frequency of an event. Randomness eventually settles to probability. Lets say you keep track…. 1 Red100% (1 out of 1) 2Green 50% (1 out of 2) 3Green 33% (1 out of 3) 4Red 50% (2 out of 4) 5Red 60% (3 out of 5) 6Green 50% (3 out of 6) Day Light is… % of time it is red

What would the graph look like over time There is no stop light elf in there watching for your car… Therefore, if the light is going to be red a certain percentage of the time, over time you should see the prediction level out.

Predicting Predicting particular results is difficult (call heads or tails on a coin toss, win vs. loss for a football pool) Long run prediction is easier for certain events (in the long run, the coin should be heads roughly 50% of the time) Each trial is an Attempt What happen is the Outcome Combination of outcomes is called the Event

Imagine this: The probability of winning Mega Millions = 1/175,711,536. Imagine 175,711,536 quarters in a row. One is purple on the underside. You will win the lottery if you pick up the quarter that is purple. How long is the row of quarters? (5280 feet in a mile) That would get us to…. Fresno CA, if we stopped in San Francisco first… (as the crow flies)

Probability egion=us Probability – the numerical measure of the likelihood of an event. 0 ≤ P(A) ≤ 1

Probability (cont) What does it mean if P(A) is close to 0? What does it mean if P(A) is close to 1? What does it mean if P(A) = 0? = 1?

Probability (cont) What does it mean if P(A) is close to 0? What does it mean if P(A) is close to 1? What does it mean if P(A) = 0? = 1?

Probability (cont) Lets try rolling dice. You keep track, and when we are all done we will put the results on a giant chart…

Predicted Frequency of 2, 12?.028 Predicted Frequency 3, 11?.056 Predicted Frequency of 4, 10?.083 Predicted Frequency of 5, 9?.111 Predicted Frequency of 6, 8?.139 Predicted Frequency of 7?.167

Probability (cont) Was your probability close to predicted? Did it get better the more sums considered? For Equally likely outcomes,

Probability (cont) Was your probability close to predicted? Did it get better the more sums considered? For Equally likely outcomes,

Probability (cont) Some Definitions Statistical Experiment (Observation) – any random activity that results in a definite outcome. Event – a collection of 1 or more outcomes of a statistical experiment Simple event – one outcome of a statistical experiment Sample Space – set of all Simple Events Sum of Probability of all Simple events = 1

Probability (contr) The complement of event A = A C = describes the event NOT occurring Therefore P(A) + P(A C ) = 1

4.2 Probability Rules Cards, Dice, etc

Dependent vs Independent First, we need to define an independent vs a dependent event. Rolling two dice Tossing two coins Drawing two cards from a deck Drawing three marbles from a bag

What is a distinguishing factor of these four things Independent events have no effect on each other. That is, tossing one coin has no impact on what you might get when you toss the second. Dependent events do. Draw a card from a deck. Can you draw this card again? Not without replacement.

Independent Events Lets look back at our dice chart. What is the probability of rolling a 6 and 1 (in that order)? What about rolling a 1 and 6 (in that order)? What is the probability of getting two sixes (chart)? What is the relationship between those numbers? P(A and B) = P(A)  P(B) Note: if A and B and C, then P(A)  P(B)  P(C) Order matters!

Dependent Events Kind of changes, but looks the same. That is, the probability of the second event will be slightly altered assuming success on the first. The basic concept is the same P(A and B) = P(A)  P(B, given A occurs) P(A and B) = P(B)  P(A, given B occurs)

Dependent Events (cont) Drawing cards from a deck, without replacement, is a Dependent event. Once you draw the Ace of Hearts, you can’t draw it again. What is the probability in Texas Hold’Em of being dealt two aces? What is the probability of being dealt two red aces?

Conditional Probability If P(A and B) = P(B)  P(A, given B), then

Conditional Probability (cont) If P(A and B) = P(B)  P(A, given B), then That bar notation means probability of A, given B has occurred…

Probability of two events happening together Back to the dice: What is the probability of getting a total of 3? Look at your chart… How many ways are there to get a 3? How does this affect probability? Probability of A or B (1 then 2 or 2 then 1) It looks like we….

Probability of two events happening together Add them.. Yes, typically P(A or B) = P(A) + P(B) As long as the events are mutually exclusive. That is, if they cannot occur together. Could one of the dice be 1 and 2 at the same time?? (P(A)+P(B)=0)

Mutually Exclusive Events Imagine a deck of cards. What is the probability of drawing a diamond OR an ace? P(diamond) + P(ace) But is there overlap? What if you draw the ace of diamonds? How many ace of diamonds are there? How to deal with this?

Mutually Exclusive Events If events are mutually exclusive, then P(A or B) = P(A) + P(B) If events are not mutually exclusive, then P(A or B) = P(A) + P(B) – P(A and B)

Back to dice What is the probability of rolling a sum greater than 7? What is the probability of rolling a sum 7 or greater? We can count on the chart, but how would it be written?

M&M’s In 2001 the maker of M&Ms decided to add another color. They surveyed kids in nearly every country and asked them to vote among purple, pink and teal. The global winner was purple. In the US and Japan the results were: PurplePinkTeal US42%19%37% Japan16%38%36%

M&M’s (cont) 1. What is the probability that a Japanese M&M’s survey respondent selected at random preferred pink or teal? 2. If we pick two Japanese respondents, what is the probability that they both selected purple? 3. If we pick three, what is the probability that at least one preferred purple?

Suspicious driving Police report that 78% of drivers stopped on suspicion of drunk driving are given a breath test, 36% a blood test, and 22% both tests. What is the probability that a randomly selected DWI suspect is given A) A test? B) A blood test or a breath test, but not both C) Neither test?

Same situation… Are a blood test and breath test mutually exclusive? Are they independent? (Independent means P(B│A)= P(B) Probability of B happening given A occurs is the same as P(B)

Same situation… Are a blood test and breath test mutually exclusive? Are they independent? (Independent means P(B│A)= P(B) Probability of B happening given A occurs is the same as P(B)

4.3 Trees and Counting

Trees Consider how many ways a team can win or lose in a season… Or how many sequences you can get if you toss a coin 3 times. Or how many ways you can ride 4 particular roller coasters at Great Adventure. A tree diagram allows you to look at all possibilities.

Trees (cont) Lets set up a tree for that last situation. The choices are El Toro, Rolling Thunder, Superman the Ultimate Flight, and Kinda Ka.

Trees (cont) By labeling each branch with an appropriate probability, you can use the tree diagram to compute probability of a particular outcome. In the reading there will be an example that discusses pulling balls out of urns. Write the probabilities as fractions on each “branch” and then use the concepts from last section to compute P(A and B)

Application According to a study by the Harvard School of Public Health, 44% of college students engage in binge drinking, 37% drink moderately and 19% abstain entirely. Another study published in the American Journal of Health Behavior, finds that among binge drinkers aged 21 to 34, 17% have been involved in alcohol related automobile accidents while among non-bingers of the same age, only 9% have been involved in such accidents. What is the probability that a randomly selected college student will be a binge drinker that has had an alcohol related car accident?

We could do this with conditional probability (That is, finding the probability of selecting someone who is a binge drinker AND a driver with an alcohol related accident) Lets look at it from a tree point of view – this is sometimes organizationally a good way to consider… It also is a good way to solve a problem that asks more than one question…

Going backwards What if you instead wanted to know if a student has an alcohol related accident, what is the probability that the student is also a binge drinker? Remember

Going backwards What if you instead wanted to know if a student has an alcohol related accident, what is the probability that the student is also a binge drinker? Remember

Tree gives P(accident | binge) but we want P(binge |accident) Using the above formula, P(binge |accident) = P(binge and accident) P(accident) =.075/.108 (remember the tree?)=69%

Trees (cont) Why does this work? The Fundamental Theorem of Counting says If there are m 1 ways to do a first task, m 2 ways to do a second task, m 3 ways to do a third task…… m n ways to do the nth task, then the total possible “patterns” or ways you could do all the tasks is m 1 · m 2 · m 3...m n

Permutations Now is the time we can introduce a few new mathematical operators (that you should already know) ! is called the factorial symbol n! = n(n-1)(n-2)(n-3)…..1 3! = 3(2)(1) = 6 5! = 5(4)(3)(2)(1)= 120 0! = 1 Calculators use a special formula to compute factorials; this is a large number formula but as result your calculator will give you an answer for 1.5! which is false

Permutations (cont) So what is a permutation? A permutation of “n” elements taken “r” at a time is an ordered arrangement (without repetition) of r of the n elements and it is called n P r.

Permutations (cont) So what is a permutation? A permutation of “n” elements taken “r” at a time is an ordered arrangement (without repetition) of r of the n elements and it is called n P r. The thing to remember is that ORDER MATTERS!!

How to recognize a permutation problem The wording will imply somehow that order matters. In how many different ways can you ride 5 out of 11 of the max rated rides at Great Adventure? “different ways” means order matters

Combinations What if order doesn’t matters? How many combinations of 5 of the 11 max rated rides at Great Adventure are there? Groupings, in which order doesn’t matter, are called combinations. Smaller or larger?

Combinations (cont) It looks like a permutation formula but with one crucial difference. A Combination n elements, r at a time, is equal to Dividing by r! gets rid of overlap