Chapter 4: Conditional Probability

Slides:



Advertisements
Similar presentations
1 Review Probability Random variables Binomial distribution.
Advertisements

Please turn off cell phones, pagers, etc. The lecture will begin shortly.
Chapter 4 Probability: Probabilities of Compound Events
Who Wants To Be A Millionaire?
0 0 Review Probability Axioms –Non-negativity P(A)≥0 –Additivity P(A U B) =P(A)+ P(B), if A and B are disjoint. –Normalization P(Ω)=1 Independence of two.
Chapter 7 Review.
BINOMIAL AND NORMAL DISTRIBUTIONS BINOMIAL DISTRIBUTION “Bernoulli trials” – experiments satisfying 3 conditions: 1. Experiment has only 2 possible outcomes:
Chapter 6: Probability : The Study of Randomness “We figured the odds as best we could, and then we rolled the dice.” US President Jimmy Carter June 10,
Section 7A: Fundamentals of Probability Section Objectives Define outcomes and event Construct a probability distribution Define subjective and empirical.
L.E.Q. How do you use segment and area models to find the probabilities of events?
Part VI: Named Continuous Random Variables
Mrs. McConaughyGeoemtric Probability Geometric Probability During this lesson, you will determine probabilities by calculating a ratio of two lengths,
Statistics Chapter 3: Introduction to Discrete Random Variables.
Quiz 3a  Probability. 1. What is the probability of selecting a spade from a deck of 52 cards? a) 1/4 b) 1/2 c) 10/52 d) 1/13.
Chapter 12: Conditional Probability & Independence 1.(12.1) Conditional Probability 2.(12.2) Independence 1.(12.1) Conditional Probability 2.(12.2) Independence.
MAT 155 Chapter 4 The following is a brief review of Chapter 4. This does NOT cover all the material in that chapter. Click on Slide Show and View Slide.
Copyright © 2009 Pearson Education, Inc. Chapter 12 Section 1 - Slide 1 P-1 Probability The Nature of Probability.
STAT 311: Introductory Probability 1.
Module 6: Continuous Probability Distributions
Section 1.2 Suppose A 1, A 2,..., A k, are k events. The k events are called mutually exclusive if The k events are called mutually exhaustive if A i 
P robability Sample Space 郭俊利 2009/02/27. Probability 2 Outline Sample space Probability axioms Conditional probability Independence 1.1 ~ 1.5.
Conditional Probabilities
Section 6.2 ~ Basics of Probability Introduction to Probability and Statistics Ms. Young.
The probability of an event based on the fact that some other event has occurred, will occur, or is occurring. P(B/A) = Conditional Probability The probability.
Formal Probability. The sum of probabilities for all possible outcomes of a trial must equal 1. Example: Flipping a Coin S = {Heads, Tails} P(H) = 0.5.
Copyright © 2015, 2011, 2008 Pearson Education, Inc. Chapter 7, Unit A, Slide 1 Probability: Living With The Odds 7.
Conditional Probability
Notes Over 12.7 Using a Normal Distribution Area Under a Curve.
Lesson Objective Understand how we can Simulate activities that have an element of chance using probabilities and random numbers Be able to use the random.
Introductory Statistics Lesson 3.1 C Objective: SSBAT find experimental probability. Standards: M11.E
8.1 Continuous Probability Distribution. Discrete Vs. Continuous Last chapter we dealt mostly with discrete data (number of things happening that usually.
Advanced Precalculus Advanced Precalculus Notes 12.3 Probability.
Conditional Probability and Independent Events
Modeling Discrete Variables Lecture 22, Part 1 Sections 6.4 Fri, Oct 13, 2006.
Chapter 7: Probability Lesson 1: Basic Principles of Probability Mrs. Parziale.
Uniform Problem A subway train on the Red Line arrives every 8 minutes during rush hour. We are interested in the length of time a commuter must wait.
Geometric probability Objective: To use segment and area models to find the probability of events.
STAT 311: Introductory Probability 1.
What is the probability of correctly guessing the outcome of exactly one out of four rolls of a die? The probability of correctly guessing one roll of.
© 2008 Pearson Addison-Wesley. All rights reserved Probability Level 8 The key idea of probability at Level 8 is investigating chance situations.
Probability Distributions. Constructing a Probability Distribution Definition: Consists of the values a random variable can assume and the corresponding.
Math 1320 Chapter 7: Probability 7.3 Probability and Probability Models.
MATHPOWER TM 12, WESTERN EDITION Chapter 9 Probability Distributions
Conditional Probability 423/what-is-your-favorite-data-analysis-cartoon 1.
Introduction to probability (4)
Chapter 15 Probability Rules!.
Past Perfect Tense.
Probability Distributions
ONE DIMENSIONAL RANDOM VARIABLES
Conditional Probability & the Multiplication Rule
13.5 Conditional Probability
Chapter 5 Review MDM 4U Mr. Lieff.
Chapter 5 Review MDM 4U Gary Greer.
AP Statistics Chapter 6 Review
Chapter 7 Lesson 8 Objective: To use segment and area models to find the probabilities of events.
Basic Probability aft A RAJASEKHAR YADAV.
Conditional Probability on a joint discrete distribution
6.2 Basics of Probability LEARNING GOAL
Probability: The study of Randomness
The Wink Game In the cup are 2 chips. One chip has a dot ( ) on it and the other chip has a dash ( ). One chip is drawn from the cup. The symbol on.
Great Theoretical Ideas In Computer Science
Week 7 Lecture 2 Chapter 13. Probability Rules.
Some Discrete Probability Distributions
Tutorial 2: Sample Space and Probability 2
6.2 Basics of Probability LEARNING GOAL
MATH 2311 Section 3.3.
Chapter 1 Expected Value.
I believe the reason students have difficulty learning algebra and that most people have trouble doing math word problems is that although children are.
Chapter 4 Probability.
Chapter 1 Probability Spaces
Presentation transcript:

Chapter 4: Conditional Probability http://imgs.xkcd.com/comics/conditional_risk.png

Example 1: Conditional Probability Roll a fair 4 sided die 3 times A = the event that two 1’s are tossed B = the event that the first roll is an 1 C = the event that the second roll is an 1 Find: P(B|A), P(A|B), P(B|C)

Example 2: Conditional Probability A bus arrives punctually at a bus stop every half hour. Each morning, a commuter named Sarah leaves her house and casually strolls to the bus stop. a) Find the probability that that wait time is at least 10 minutes. b) Find the probability that the wait time is at least 10 minutes given that if someone is waiting there for more than 15 minutes, they will get a ride from a passing car. c) Find the probability that the wait time is at most 10 minutes given that if someone is waiting there for more than 15 minutes, they will get a ride from a passing car.

Example 3: Conditional Probability 1) From the set of all families with two children, a family is selected at random and is found to have a girl. What is the probability that the other child of the family is a girl? 2) From the set of all families with two children, a child is selected at random and is found to be a girl. What is the probability that the other child of the family is a girl?

Theorem 4.10: Distributive Laws For any events, A1, A2, …

Example: Conditional Probabilities - Axioms Assume that the probability that there will be more than 1 inch of snow next week given that the temperature rises above 30 oF is 0.3. a) What is the probability that there will be less than 1 inch of snow next week given that the temperature rises above 30 oF? b) Given that the probability that there will be more than 2 inches of rain given that the temperature rises above 30 oF is 0.8 and the probability that there will be more than 2 inches of rain and there will be less than 1 inch of snow given that the temperature rises above 30 oF is 0.6, what is the probability that there will be more than 2 inches of rain or there will be less than 1 inch of snow given that the temperature rises above 30 oF?