AP Review Day 2: Discrete Probability. Basic Probability Sample space = all possible outcomes P(A c ) = 1 – P(A) Probabilities have to be between 0 and.

Slides:



Advertisements
Similar presentations
Probability Distribution
Advertisements

1 Set #3: Discrete Probability Functions Define: Random Variable – numerical measure of the outcome of a probability experiment Value determined by chance.
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 4-1 Introduction to Statistics Chapter 5 Random Variables.
Visualizing Events Contingency Tables Tree Diagrams Ace Not Ace Total Red Black Total
5.2B TWO-WAY TABLES, GENERAL ADDITION RULE AND VENN DIAGRAMS
Learning Goal 13: Probability Use the basic laws of probability by finding the probabilities of mutually exclusive events. Find the probabilities of dependent.
Mutually Exclusive: P(not A) = 1- P(A) Complement Rule: P(A and B) = 0 P(A or B) = P(A) + P(B) - P(A and B) General Addition Rule: Conditional Probability:
Key Concepts of the Probability Unit
Probability Rules l Rule 1. The probability of any event (A) is a number between zero and one. 0 < P(A) < 1.
5.2A Probability Rules! AP Statistics.
Binomial Distributions
McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 4 and 5 Probability and Discrete Random Variables.
Binomial and Geometric Distributions Notes on your own paper.
Day 2 Review Chapters 5 – 7 Probability, Random Variables, Sampling Distributions.
AP Statistics Exam Review
Chapter 7 Lesson 7.5 Random Variables and Probability Distributions
Using Probability and Discrete Probability Distributions
1 Chapters 6-8. UNIT 2 VOCABULARY – Chap 6 2 ( 2) THE NOTATION “P” REPRESENTS THE TRUE PROBABILITY OF AN EVENT HAPPENING, ACCORDING TO AN IDEAL DISTRIBUTION.
Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter 4 Probability.
AP Statistics Chapter 6 Notes. Probability Terms Random: Individual outcomes are uncertain, but there is a predictable distribution of outcomes in the.
Biostat. 200 Review slides Week 1-3. Recap: Probability.
Random Experiment Random Variable: Continuous, Discrete Sample Space: S Event: A, B, E Null Event Complement of an Event A’ Union of Events (either, or)
Chapter 12 Probability. Chapter 12 The probability of an occurrence is written as P(A) and is equal to.
Summary -1 Chapters 2-6 of DeCoursey. Basic Probability (Chapter 2, W.J.Decoursey, 2003) Objectives: -Define probability and its relationship to relative.
Probability(C14-C17 BVD) C15: Probability Rules. * OR – In probability language, OR means that either event happening or both events happening in a single.
Dr. Omar Al Jadaan Probability. Simple Probability Possibilities and Outcomes Expressed in the form of a fraction A/B Where A is the occurrence B is possible.
Probability Definition: Probability: the chance an event will happen. # of ways a certain event can occur # of possible events Probability =  Probability.
1 RES 341 RESEARCH AND EVALUATION WORKSHOP 4 By Dr. Serhat Eren University OF PHOENIX Spring 2002.
Probability You’ll probably like it!. Probability Definitions Probability assignment Complement, union, intersection of events Conditional probability.
12/7/20151 Math b Conditional Probability, Independency, Bayes Theorem.
Probability Rules. We start with four basic rules of probability. They are simple, but you must know them. Rule 1: All probabilities are numbers between.
Probability. Rules  0 ≤ P(A) ≤ 1 for any event A.  P(S) = 1  Complement: P(A c ) = 1 – P(A)  Addition: If A and B are disjoint events, P(A or B) =
AP Statistics Semester One Review Part 2 Chapters 4-6 Semester One Review Part 2 Chapters 4-6.
Notes – Chapter 17 Binomial & Geometric Distributions.
1 7.3 RANDOM VARIABLES When the variables in question are quantitative, they are known as random variables. A random variable, X, is a quantitative variable.
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 5 Probability: What Are the Chances? 5.2.
4-3 Addition Rule This section presents the addition rule as a device for finding probabilities that can be expressed as P(A or B), the probability that.
Chapter 14 From Randomness to Probability. Dealing with Random Phenomena A random phenomenon: if we know what outcomes could happen, but not which particular.
I can find probabilities of compound events.. Compound Events  Involves two or more things happening at once.  Uses the words “and” & “or”
Welcome to MM305 Unit 3 Seminar Prof Greg Probability Concepts and Applications.
STATISTICS 6.0 Conditional Probabilities “Conditional Probabilities”
© 2013 Pearson Education, Inc. Reading Quiz For use with Classroom Response Systems Introductory Statistics: Exploring the World through Data, 1e by Gould.
BUSA Probability. Probability – the bedrock of randomness Definitions Random experiment – observing the close of the NYSE and the Nasdaq Sample.
Conditional Probability If two events are not mutually exclusive, the fact that we know that B has happened will have an effect on the probability of A.
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter 4 Probability.
Chapter 15: Probability Rules! Ryan Vu and Erick Li Period 2.
B Heard Not to be used, posted, etc. without my expressed permission. B Heard.
Probability Assignment #41 Review Paper #1 day7. Probability A#41 Review Paper #1 day7.
Review Day 2 May 4 th Probability Events are independent if the outcome of one event does not influence the outcome of any other event Events are.
Probability Rules Chapter 15. Sample Space The sample space of a trial is the set of all possible outcomes and is labeled S. The outcomes do NOT need.
Key Concepts of the Probability Unit Simulation Probability rules Counting and tree diagrams Intersection (“and”): the multiplication rule, and independent.
Unit 3: Probability.  You will need to be able to describe how you will perform a simulation  Create a correspondence between random numbers and outcomes.
Conditional Probability 423/what-is-your-favorite-data-analysis-cartoon 1.
Chapter 7 Lesson 7.5 Random Variables and Probability Distributions
CHAPTER 5 Probability: What Are the Chances?
Chapter 3 Probability.
CHAPTER 5 Probability: What Are the Chances?
Chapter 4 Probability.
Business Statistics Topic 4
AP Statistics Chapter 16.
CHAPTER 5 Probability: What Are the Chances?
CHAPTER 5 Probability: What Are the Chances?
CHAPTER 5 Probability: What Are the Chances?
CHAPTER 5 Probability: What Are the Chances?
Bernoulli Trials Two Possible Outcomes Trials are independent.
CHAPTER 5 Probability: What Are the Chances?
Probability Rules Rule 1.
CHAPTER 5 Probability: What Are the Chances?
Chapter 3 & 4 Notes.
Chapter 5 – Probability Rules
Presentation transcript:

AP Review Day 2: Discrete Probability

Basic Probability Sample space = all possible outcomes P(A c ) = 1 – P(A) Probabilities have to be between 0 and 1 Sum of all possibilities has to = 1

AND/OR AND: – If A and B are independent, then P(A and B) = P(A) · P(B) – If A and B are not independent, use the General Multiplication Rule: P(A and B) = P(A) · P(B|A) Conditional Probability: – P(B|A) = the probability of B given A

AND/OR OR: – If A and B are disjoint(mutually exclusive), then P(A or B) = P(A) + P(B) – If A and B overlap, use the General Addition Rule: P(A or B) = P(A) + P(B) – P(A∩B) Disjoint/Mutually ExclusiveNon-Disjoint/Not Mutually Exclusive

From a Table P(Liberal) = P(Male) = P(Liberal|Male) = LiberalModerateConservativeTotal Male Female Total

Independence If two events are independent, then In other words, knowing A is true doesn’t change the probability of B Since P(Liberal) ≠ P(Liberal|Male), gender and political identification are not independent

Probability Distributions Has to add up to 1 These formulas are on your formula sheet Don’t forget X P(X)

Combining Distributions For means, just do whatever you do to the variables: For standard deviations, use these rules:

Binomial Requirements: 1)2 possible outcomes (success/failure) 2)Fixed number of trials (n) 3)Each trial is independent 4)Probability of success (p) stays the same for each trial DISTR menu on calculator (write binomial, with n= and p=)