EPE / EDP 557 Homework 7

Size: px
Start display at page:

Download "EPE / EDP 557 Homework 7"

Transcription

1 Section III. A. Questions EPE / EDP 557 Homework 7 Section III. A. and Lab 7 Suppose you roll a die once and flip a coin twice. Events are defined as follows: A = {Die is a 1} B = {Both flips of the coin are Tails}. Use this scenario to answer questions ) How many possible outcomes are there? 2) Give the sample space (Recommendation: use a table and let the columns of the table represent the outcomes when rolling the die and let the rows of the table represent the outcomes when flipping the coin twice). 3) Find P A 4) Find P B 5) Find P A 6) Find P Aand B 7) Find P A or B 8) Find P A B 9) Are events A and B mutually exclusive? 10) Are events A and B independent?

2 Use the Contingency Table above to answer questions Events are defined as follows: A = {Individual is Male} and B = {Individual weight is About Right} 11) Find 12) Find P A P B 13) Find P B 14) Find P B and A 15) Find P B or A 16) Find P B A 17) Are events A and B mutually exclusive? 18) Are events A and B independent? Suppose you have a bag with 5 red, 7 white, 3 blue poker chips. Use this information to answer questions ) If you draw four chips with replacement, what is the probability that all four are white? 20) If you draw four chips without replacement, what is the probability that all four are white? 21) If you draw four chips without replacement, what is the probability that at least one of the chips are not white?

3 Lab 7 Identifying Variable Frequencies Open the Student Survey Data. Create a Contingency Table for the variables Sport and Hand Select Analyze > Descriptive Statistics > Crosstabs. For the Row(s): choose Sport and for the Column(s): choose Hand. Click OK. Create a Contingency Table for the variables Eye and Travel Select Analyze > Descriptive Statistics > Crosstabs. For the Row(s): choose Eye and for the Column(s): choose Travel. Click OK. Create a Frequency Table for the variables Flip1-Flip10 and the variables Roll1-Roll10 Select Analyze > Descriptive Statistics > Frequencies. Under Variables(s): choose the variables Flip1-Flip10 and Roll1-Roll10 (there will be 20 variables so 20 tables will be created). To select all these variables at once click on Flip1, hold down shift key, click on Roll10, and then use the arrow to select them. Click OK.

4 SHORT ANSWER WRITING ASSIGNMENT 22) Use the Contingency Table created for the variables hand and sport to find the probabilities below. The events are defined as follows: A basketball is favorite sport and B left handed. a. b. c. d. P P A B P A P B e. P Aand B f. P A or B P A B g. h. P B A 23) Use the Contingency Table created for the variables hand and sport to answer the questions below. The events are defined as follows: A basketball is favorite sport and B left handed. a. Are events A and B mutually exclusive? Explain. b. Are events A and B dependent or independent? Explain. 24) Use the Contingency Table created for the variables eye and travel to find the probabilities below (when identified use probability rule to find probability). The events are defined as brown eyes B drive toschool. follows: A and a. P A b. P B c. Complement rule: P A d. Complement rule: P B e. P Aand B f. Addition rule: P A or B g. Conditional Probability rule: P A B h. Conditional Probability rule: P B A 25) Use the Contingency Table created for the variables eye and travel to answer the questions below. The events are defined as follows: A brown eyes and B drive toschool. a. Are events A and B mutually exclusive? Explain. b. Are events A and B dependent or independent? Explain.

5 26) Use the Frequency Tables for the variables Flip1-Flip10 to fill out the following table. In the last column of the table, calculate the probability of getting tails based on the frequency. Variable Number of Tails Number of Flips Probability of Tails Flip1 Flip2 Flip3 Flip4 Flip5 Flip6 Flip7 Flip8 Flip9 Flip10 27) Use the table created in question 26 for the following: a. If you flip a coin, what is the probability of getting tails (true probability not from table)? It is important to think about inferential statistics as we cover the topics included in the probability unit. In this situation the probability (same as proportion or percentage) of getting tails is like the parameter in a study. It is an exact value that we can only calculate by knowing the population. b. Explain why the probabilities calculated in the table are not all the same. In terms of inferential statistics, each probability from the table could be thought of as a statistic. The data was selected randomly because each time a coin was flipped a random outcome was selected. The probability (same as proportion or percentage) was then calculated. c. Explain why the probabilities calculated in the table are not equal to the true probability (part a above) of getting tails?

6 28) Use the Frequency Tables for the variables Roll1-Roll10 to fill out the following table. In the last column of the table, calculate the probability of getting a six based on the frequency. Variable Number of Sixes Number of Rolls Probability of a Six Roll1 Roll2 Roll3 Roll4 Roll5 Roll6 Roll7 Roll8 Roll9 Roll10 29) Use the table created in question 28 for the following: a. If you roll a die, what is the probability of getting a six (true probability not from table)? b. Explain how comparing the true probability of getting a six (part a above) to the above table is the same as what was illustrated in question 27 of this lab? c. What is different in this situation as compared to question 27 of this lab?

Math 243 Section 3.1 Introduction to Probability Lab

Math 243 Section 3.1 Introduction to Probability Lab Math 243 Section 3.1 Introduction to Probability Lab Overview Why Study Probability? Outcomes, Events, Sample Space, Trials Probabilities and Complements (not) Theoretical vs. Empirical Probability The

More information

Chapter 5 : Probability. Exercise Sheet. SHilal. 1 P a g e

Chapter 5 : Probability. Exercise Sheet. SHilal. 1 P a g e 1 P a g e experiment ( observing / measuring ) outcomes = results sample space = set of all outcomes events = subset of outcomes If we collect all outcomes we are forming a sample space If we collect some

More information

CHAPTER 3 PROBABILITY TOPICS

CHAPTER 3 PROBABILITY TOPICS CHAPTER 3 PROBABILITY TOPICS 1. Terminology In this chapter, we are interested in the probability of a particular event occurring when we conduct an experiment. The sample space of an experiment is the

More information

Chapter 7 Wednesday, May 26th

Chapter 7 Wednesday, May 26th Chapter 7 Wednesday, May 26 th Random event A random event is an event that the outcome is unpredictable. Example: There are 45 students in this class. What is the probability that if I select one student,

More information

Mutually Exclusive Events

Mutually Exclusive Events 172 CHAPTER 3 PROBABILITY TOPICS c. QS, 7D, 6D, KS Mutually Exclusive Events A and B are mutually exclusive events if they cannot occur at the same time. This means that A and B do not share any outcomes

More information

Probability- describes the pattern of chance outcomes

Probability- describes the pattern of chance outcomes Chapter 6 Probability the study of randomness Probability- describes the pattern of chance outcomes Chance behavior is unpredictable in the short run, but has a regular and predictable pattern in the long

More information

Intermediate Math Circles November 8, 2017 Probability II

Intermediate Math Circles November 8, 2017 Probability II Intersection of Events and Independence Consider two groups of pairs of events Intermediate Math Circles November 8, 017 Probability II Group 1 (Dependent Events) A = {a sales associate has training} B

More information

Sets and Set notation. Algebra 2 Unit 8 Notes

Sets and Set notation. Algebra 2 Unit 8 Notes Sets and Set notation Section 11-2 Probability Experimental Probability experimental probability of an event: Theoretical Probability number of time the event occurs P(event) = number of trials Sample

More information

Probability Year 9. Terminology

Probability Year 9. Terminology Probability Year 9 Terminology Probability measures the chance something happens. Formally, we say it measures how likely is the outcome of an event. We write P(result) as a shorthand. An event is some

More information

Math 1313 Experiments, Events and Sample Spaces

Math 1313 Experiments, Events and Sample Spaces Math 1313 Experiments, Events and Sample Spaces At the end of this recording, you should be able to define and use the basic terminology used in defining experiments. Terminology The next main topic in

More information

Probability Year 10. Terminology

Probability Year 10. Terminology Probability Year 10 Terminology Probability measures the chance something happens. Formally, we say it measures how likely is the outcome of an event. We write P(result) as a shorthand. An event is some

More information

Chapter 6: Probability The Study of Randomness

Chapter 6: Probability The Study of Randomness Chapter 6: Probability The Study of Randomness 6.1 The Idea of Probability 6.2 Probability Models 6.3 General Probability Rules 1 Simple Question: If tossing a coin, what is the probability of the coin

More information

A brief review of basics of probabilities

A brief review of basics of probabilities brief review of basics of probabilities Milos Hauskrecht milos@pitt.edu 5329 Sennott Square robability theory Studies and describes random processes and their outcomes Random processes may result in multiple

More information

3 PROBABILITY TOPICS

3 PROBABILITY TOPICS Chapter 3 Probability Topics 135 3 PROBABILITY TOPICS Figure 3.1 Meteor showers are rare, but the probability of them occurring can be calculated. (credit: Navicore/flickr) Introduction It is often necessary

More information

Math 140 Introductory Statistics

Math 140 Introductory Statistics Math 140 Introductory Statistics 5.1 Models of random behavior Outcome: Result or answer obtained from a chance process. Event: Collection of outcomes. Probability: Number between 0 and 1 (0% and 100%).

More information

Topic -2. Probability. Larson & Farber, Elementary Statistics: Picturing the World, 3e 1

Topic -2. Probability. Larson & Farber, Elementary Statistics: Picturing the World, 3e 1 Topic -2 Probability Larson & Farber, Elementary Statistics: Picturing the World, 3e 1 Probability Experiments Experiment : An experiment is an act that can be repeated under given condition. Rolling a

More information

Fundamentals of Probability CE 311S

Fundamentals of Probability CE 311S Fundamentals of Probability CE 311S OUTLINE Review Elementary set theory Probability fundamentals: outcomes, sample spaces, events Outline ELEMENTARY SET THEORY Basic probability concepts can be cast in

More information

The probability of an event is viewed as a numerical measure of the chance that the event will occur.

The probability of an event is viewed as a numerical measure of the chance that the event will occur. Chapter 5 This chapter introduces probability to quantify randomness. Section 5.1: How Can Probability Quantify Randomness? The probability of an event is viewed as a numerical measure of the chance that

More information

Basic Concepts of Probability

Basic Concepts of Probability Probability Probability theory is the branch of math that deals with random events Probability is used to describe how likely a particular outcome is in a random event the probability of obtaining heads

More information

I - Probability. What is Probability? the chance of an event occuring. 1classical probability. 2empirical probability. 3subjective probability

I - Probability. What is Probability? the chance of an event occuring. 1classical probability. 2empirical probability. 3subjective probability What is Probability? the chance of an event occuring eg 1classical probability 2empirical probability 3subjective probability Section 2 - Probability (1) Probability - Terminology random (probability)

More information

Basic Concepts of Probability

Basic Concepts of Probability Probability Probability theory is the branch of math that deals with unpredictable or random events Probability is used to describe how likely a particular outcome is in a random event the probability

More information

Problem # Number of points 1 /20 2 /20 3 /20 4 /20 5 /20 6 /20 7 /20 8 /20 Total /150

Problem # Number of points 1 /20 2 /20 3 /20 4 /20 5 /20 6 /20 7 /20 8 /20 Total /150 Name Student ID # Instructor: SOLUTION Sergey Kirshner STAT 516 Fall 09 Practice Midterm #1 January 31, 2010 You are not allowed to use books or notes. Non-programmable non-graphic calculators are permitted.

More information

Topic 2 Probability. Basic probability Conditional probability and independence Bayes rule Basic reliability

Topic 2 Probability. Basic probability Conditional probability and independence Bayes rule Basic reliability Topic 2 Probability Basic probability Conditional probability and independence Bayes rule Basic reliability Random process: a process whose outcome can not be predicted with certainty Examples: rolling

More information

Independence Solutions STAT-UB.0103 Statistics for Business Control and Regression Models

Independence Solutions STAT-UB.0103 Statistics for Business Control and Regression Models Independence Solutions STAT-UB.003 Statistics for Business Control and Regression Models The Birthday Problem. A class has 70 students. What is the probability that at least two students have the same

More information

Topic 5: Probability. 5.4 Combined Events and Conditional Probability Paper 1

Topic 5: Probability. 5.4 Combined Events and Conditional Probability Paper 1 Topic 5: Probability Standard Level 5.4 Combined Events and Conditional Probability Paper 1 1. In a group of 16 students, 12 take art and 8 take music. One student takes neither art nor music. The Venn

More information

Chapter 7: Section 7-1 Probability Theory and Counting Principles

Chapter 7: Section 7-1 Probability Theory and Counting Principles Chapter 7: Section 7-1 Probability Theory and Counting Principles D. S. Malik Creighton University, Omaha, NE D. S. Malik Creighton University, Omaha, NE Chapter () 7: Section 7-1 Probability Theory and

More information

The enumeration of all possible outcomes of an experiment is called the sample space, denoted S. E.g.: S={head, tail}

The enumeration of all possible outcomes of an experiment is called the sample space, denoted S. E.g.: S={head, tail} Random Experiment In random experiments, the result is unpredictable, unknown prior to its conduct, and can be one of several choices. Examples: The Experiment of tossing a coin (head, tail) The Experiment

More information

Presentation on Theo e ry r y o f P r P o r bab a il i i l t i y

Presentation on Theo e ry r y o f P r P o r bab a il i i l t i y Presentation on Theory of Probability Meaning of Probability: Chance of occurrence of any event In practical life we come across situation where the result are uncertain Theory of probability was originated

More information

Probability deals with modeling of random phenomena (phenomena or experiments whose outcomes may vary)

Probability deals with modeling of random phenomena (phenomena or experiments whose outcomes may vary) Chapter 14 From Randomness to Probability How to measure a likelihood of an event? How likely is it to answer correctly one out of two true-false questions on a quiz? Is it more, less, or equally likely

More information

Discussion 01. b) What is the probability that the letter selected is a vowel?

Discussion 01. b) What is the probability that the letter selected is a vowel? STAT 400 Discussion 01 Spring 2018 1. Consider the following experiment: A letter is chosen at random from the word STATISTICS. a) List all possible outcomes and their probabilities. b) What is the probability

More information

MATH 3C: MIDTERM 1 REVIEW. 1. Counting

MATH 3C: MIDTERM 1 REVIEW. 1. Counting MATH 3C: MIDTERM REVIEW JOE HUGHES. Counting. Imagine that a sports betting pool is run in the following way: there are 20 teams, 2 weeks, and each week you pick a team to win. However, you can t pick

More information

Problems from Probability and Statistical Inference (9th ed.) by Hogg, Tanis and Zimmerman.

Problems from Probability and Statistical Inference (9th ed.) by Hogg, Tanis and Zimmerman. Math 224 Fall 2017 Homework 1 Drew Armstrong Problems from Probability and Statistical Inference (9th ed.) by Hogg, Tanis and Zimmerman. Section 1.1, Exercises 4,5,6,7,9,12. Solutions to Book Problems.

More information

k P (X = k)

k P (X = k) Math 224 Spring 208 Homework Drew Armstrong. Suppose that a fair coin is flipped 6 times in sequence and let X be the number of heads that show up. Draw Pascal s triangle down to the sixth row (recall

More information

Week 2. Section Texas A& M University. Department of Mathematics Texas A& M University, College Station 22 January-24 January 2019

Week 2. Section Texas A& M University. Department of Mathematics Texas A& M University, College Station 22 January-24 January 2019 Week 2 Section 1.2-1.4 Texas A& M University Department of Mathematics Texas A& M University, College Station 22 January-24 January 2019 Oğuz Gezmiş (TAMU) Topics in Contemporary Mathematics II Week2 1

More information

Axioms of Probability. Set Theory. M. Bremer. Math Spring 2018

Axioms of Probability. Set Theory. M. Bremer. Math Spring 2018 Math 163 - pring 2018 Axioms of Probability Definition: The set of all possible outcomes of an experiment is called the sample space. The possible outcomes themselves are called elementary events. Any

More information

Chap 4 Probability p227 The probability of any outcome in a random phenomenon is the proportion of times the outcome would occur in a long series of

Chap 4 Probability p227 The probability of any outcome in a random phenomenon is the proportion of times the outcome would occur in a long series of Chap 4 Probability p227 The probability of any outcome in a random phenomenon is the proportion of times the outcome would occur in a long series of repetitions. (p229) That is, probability is a long-term

More information

2.4. Conditional Probability

2.4. Conditional Probability 2.4. Conditional Probability Objectives. Definition of conditional probability and multiplication rule Total probability Bayes Theorem Example 2.4.1. (#46 p.80 textbook) Suppose an individual is randomly

More information

14 - PROBABILITY Page 1 ( Answers at the end of all questions )

14 - PROBABILITY Page 1 ( Answers at the end of all questions ) - PROBABILITY Page ( ) Three houses are available in a locality. Three persons apply for the houses. Each applies for one house without consulting others. The probability that all the three apply for the

More information

When working with probabilities we often perform more than one event in a sequence - this is called a compound probability.

When working with probabilities we often perform more than one event in a sequence - this is called a compound probability. + Independence + Compound Events When working with probabilities we often perform more than one event in a sequence - this is called a compound probability. Compound probabilities are more complex than

More information

Math 140 Introductory Statistics

Math 140 Introductory Statistics 5. Models of Random Behavior Math 40 Introductory Statistics Professor Silvia Fernández Chapter 5 Based on the book Statistics in Action by A. Watkins, R. Scheaffer, and G. Cobb. Outcome: Result or answer

More information

Math 140 Introductory Statistics

Math 140 Introductory Statistics Math 140 Introductory Statistics Professor Silvia Fernández Lecture 8 Based on the book Statistics in Action by A. Watkins, R. Scheaffer, and G. Cobb. 5.1 Models of Random Behavior Outcome: Result or answer

More information

Basic Statistics and Probability Chapter 3: Probability

Basic Statistics and Probability Chapter 3: Probability Basic Statistics and Probability Chapter 3: Probability Events, Sample Spaces and Probability Unions and Intersections Complementary Events Additive Rule. Mutually Exclusive Events Conditional Probability

More information

STA 291 Lecture 8. Probability. Probability Rules. Joint and Marginal Probability. STA Lecture 8 1

STA 291 Lecture 8. Probability. Probability Rules. Joint and Marginal Probability. STA Lecture 8 1 STA 291 Lecture 8 Probability Probability Rules Joint and Marginal Probability STA 291 - Lecture 8 1 Union and Intersection Let A and B denote two events. The union of two events: A B The intersection

More information

Chapter 2.5 Random Variables and Probability The Modern View (cont.)

Chapter 2.5 Random Variables and Probability The Modern View (cont.) Chapter 2.5 Random Variables and Probability The Modern View (cont.) I. Statistical Independence A crucially important idea in probability and statistics is the concept of statistical independence. Suppose

More information

Independence 1 2 P(H) = 1 4. On the other hand = P(F ) =

Independence 1 2 P(H) = 1 4. On the other hand = P(F ) = Independence Previously we considered the following experiment: A card is drawn at random from a standard deck of cards. Let H be the event that a heart is drawn, let R be the event that a red card is

More information

Axioms of Probability

Axioms of Probability Sample Space (denoted by S) The set of all possible outcomes of a random experiment is called the Sample Space of the experiment, and is denoted by S. Example 1.10 If the experiment consists of tossing

More information

CMPSCI 240: Reasoning about Uncertainty

CMPSCI 240: Reasoning about Uncertainty CMPSCI 240: Reasoning about Uncertainty Lecture 2: Sets and Events Andrew McGregor University of Massachusetts Last Compiled: January 27, 2017 Outline 1 Recap 2 Experiments and Events 3 Probabilistic Models

More information

Probability and Statistics Notes

Probability and Statistics Notes Probability and Statistics Notes Chapter One Jesse Crawford Department of Mathematics Tarleton State University (Tarleton State University) Chapter One Notes 1 / 71 Outline 1 A Sketch of Probability and

More information

PRACTICE PROBLEMS FOR EXAM 2

PRACTICE PROBLEMS FOR EXAM 2 PRACTICE PROBLEMS FOR EXAM 2 Math 3160Q Fall 2015 Professor Hohn Below is a list of practice questions for Exam 2. Any quiz, homework, or example problem has a chance of being on the exam. For more practice,

More information

Year 10 Mathematics Probability Practice Test 1

Year 10 Mathematics Probability Practice Test 1 Year 10 Mathematics Probability Practice Test 1 1 A letter is chosen randomly from the word TELEVISION. a How many letters are there in the word TELEVISION? b Find the probability that the letter is: i

More information

STAT 430/510 Probability

STAT 430/510 Probability STAT 430/510 Probability Hui Nie Lecture 3 May 28th, 2009 Review We have discussed counting techniques in Chapter 1. Introduce the concept of the probability of an event. Compute probabilities in certain

More information

UNIT 5 ~ Probability: What Are the Chances? 1

UNIT 5 ~ Probability: What Are the Chances? 1 UNIT 5 ~ Probability: What Are the Chances? 1 6.1: Simulation Simulation: The of chance behavior, based on a that accurately reflects the phenomenon under consideration. (ex 1) Suppose we are interested

More information

Statistics for Managers Using Microsoft Excel (3 rd Edition)

Statistics for Managers Using Microsoft Excel (3 rd Edition) Statistics for Managers Using Microsoft Excel (3 rd Edition) Chapter 4 Basic Probability and Discrete Probability Distributions 2002 Prentice-Hall, Inc. Chap 4-1 Chapter Topics Basic probability concepts

More information

Lecture 3 Probability Basics

Lecture 3 Probability Basics Lecture 3 Probability Basics Thais Paiva STA 111 - Summer 2013 Term II July 3, 2013 Lecture Plan 1 Definitions of probability 2 Rules of probability 3 Conditional probability What is Probability? Probability

More information

Counting Rules. Counting operations on n objects. Sort, order matters (perms) Choose k (combinations) Put in r buckets. None Distinct.

Counting Rules. Counting operations on n objects. Sort, order matters (perms) Choose k (combinations) Put in r buckets. None Distinct. Probability Counting Rules Counting operations on n objects Sort, order matters (perms) Choose k (combinations) Put in r buckets Distinct n! Some Distinct n! n 1!n 2!... n k Distinct = n! k!(n k)! Distinct

More information

CINQA Workshop Probability Math 105 Silvia Heubach Department of Mathematics, CSULA Thursday, September 6, 2012

CINQA Workshop Probability Math 105 Silvia Heubach Department of Mathematics, CSULA Thursday, September 6, 2012 CINQA Workshop Probability Math 105 Silvia Heubach Department of Mathematics, CSULA Thursday, September 6, 2012 Silvia Heubach/CINQA 2012 Workshop Objectives To familiarize biology faculty with one of

More information

Section 13.3 Probability

Section 13.3 Probability 288 Section 13.3 Probability Probability is a measure of how likely an event will occur. When the weather forecaster says that there will be a 50% chance of rain this afternoon, the probability that it

More information

4. Probability of an event A for equally likely outcomes:

4. Probability of an event A for equally likely outcomes: University of California, Los Angeles Department of Statistics Statistics 110A Instructor: Nicolas Christou Probability Probability: A measure of the chance that something will occur. 1. Random experiment:

More information

Probability and Discrete Distributions

Probability and Discrete Distributions AMS 7L LAB #3 Fall, 2007 Objectives: Probability and Discrete Distributions 1. To explore relative frequency and the Law of Large Numbers 2. To practice the basic rules of probability 3. To work with the

More information

Probability: Part 2 *

Probability: Part 2 * OpenStax-CNX module: m39373 1 Probability: Part 2 * Free High School Science Texts Project This work is produced by OpenStax-CNX and licensed under the Creative Commons Attribution License 3.0 1 Relative

More information

STAT 111 Recitation 1

STAT 111 Recitation 1 STAT 111 Recitation 1 Linjun Zhang January 20, 2017 What s in the recitation This class, and the exam of this class, is a mix of statistical concepts and calculations. We are going to do a little bit of

More information

Lecture 5: Introduction to Markov Chains

Lecture 5: Introduction to Markov Chains Lecture 5: Introduction to Markov Chains Winfried Just Department of Mathematics, Ohio University January 24 26, 2018 weather.com light The weather is a stochastic process. For now we can assume that this

More information

Chapter 14. From Randomness to Probability. Copyright 2012, 2008, 2005 Pearson Education, Inc.

Chapter 14. From Randomness to Probability. Copyright 2012, 2008, 2005 Pearson Education, Inc. Chapter 14 From Randomness to Probability Copyright 2012, 2008, 2005 Pearson Education, Inc. Dealing with Random Phenomena A random phenomenon is a situation in which we know what outcomes could happen,

More information

Data 1 Assessment Calculator allowed for all questions

Data 1 Assessment Calculator allowed for all questions Foundation Higher Data Assessment Calculator allowed for all questions MATHSWATCH All questions Time for the test: 45 minutes Name: Grade Title of clip Marks Score Percentage Clip 84 D Data collection

More information

P (A) = P (B) = P (C) = P (D) =

P (A) = P (B) = P (C) = P (D) = STAT 145 CHAPTER 12 - PROBABILITY - STUDENT VERSION The probability of a random event, is the proportion of times the event will occur in a large number of repititions. For example, when flipping a coin,

More information

4. Suppose that we roll two die and let X be equal to the maximum of the two rolls. Find P (X {1, 3, 5}) and draw the PMF for X.

4. Suppose that we roll two die and let X be equal to the maximum of the two rolls. Find P (X {1, 3, 5}) and draw the PMF for X. Math 10B with Professor Stankova Worksheet, Midterm #2; Wednesday, 3/21/2018 GSI name: Roy Zhao 1 Problems 1.1 Bayes Theorem 1. Suppose a test is 99% accurate and 1% of people have a disease. What is the

More information

Announcements. Lecture 5: Probability. Dangling threads from last week: Mean vs. median. Dangling threads from last week: Sampling bias

Announcements. Lecture 5: Probability. Dangling threads from last week: Mean vs. median. Dangling threads from last week: Sampling bias Recap Announcements Lecture 5: Statistics 101 Mine Çetinkaya-Rundel September 13, 2011 HW1 due TA hours Thursday - Sunday 4pm - 9pm at Old Chem 211A If you added the class last week please make sure to

More information

Conditional Probability 2 Solutions COR1-GB.1305 Statistics and Data Analysis

Conditional Probability 2 Solutions COR1-GB.1305 Statistics and Data Analysis Conditional Probability 2 Solutions COR-GB.305 Statistics and Data Analysis The Birthday Problem. A class has 50 students. What is the probability that at least two students have the same birthday? Assume

More information

Lecture 8: Conditional probability I: definition, independence, the tree method, sampling, chain rule for independent events

Lecture 8: Conditional probability I: definition, independence, the tree method, sampling, chain rule for independent events Lecture 8: Conditional probability I: definition, independence, the tree method, sampling, chain rule for independent events Discrete Structures II (Summer 2018) Rutgers University Instructor: Abhishek

More information

Properties of Probability

Properties of Probability Econ 325 Notes on Probability 1 By Hiro Kasahara Properties of Probability In statistics, we consider random experiments, experiments for which the outcome is random, i.e., cannot be predicted with certainty.

More information

Intro to Probability Day 3 (Compound events & their probabilities)

Intro to Probability Day 3 (Compound events & their probabilities) Intro to Probability Day 3 (Compound events & their probabilities) Compound Events Let A, and B be two event. Then we can define 3 new events as follows: 1) A or B (also A B ) is the list of all outcomes

More information

Monty Hall Puzzle. Draw a tree diagram of possible choices (a possibility tree ) One for each strategy switch or no-switch

Monty Hall Puzzle. Draw a tree diagram of possible choices (a possibility tree ) One for each strategy switch or no-switch Monty Hall Puzzle Example: You are asked to select one of the three doors to open. There is a large prize behind one of the doors and if you select that door, you win the prize. After you select a door,

More information

20.2 Independent Events

20.2 Independent Events Name Class Date 20.2 Independent Events Essential Question: What does it mean for two events to be independent? Explore Understanding the Independence of Events Resource Locker Suppose you flip a coin

More information

Ch 14 Randomness and Probability

Ch 14 Randomness and Probability Ch 14 Randomness and Probability We ll begin a new part: randomness and probability. This part contain 4 chapters: 14-17. Why we need to learn this part? Probability is not a portion of statistics. Instead

More information

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 2 MATH00040 SEMESTER / Probability

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 2 MATH00040 SEMESTER / Probability ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 2 MATH00040 SEMESTER 2 2017/2018 DR. ANTHONY BROWN 5.1. Introduction to Probability. 5. Probability You are probably familiar with the elementary

More information

Econ 113. Lecture Module 2

Econ 113. Lecture Module 2 Econ 113 Lecture Module 2 Contents 1. Experiments and definitions 2. Events and probabilities 3. Assigning probabilities 4. Probability of complements 5. Conditional probability 6. Statistical independence

More information

Conditional Probability

Conditional Probability Conditional Probability When we obtain additional information about a probability experiment, we want to use the additional information to reassess the probabilities of events given the new information.

More information

4 Lecture 4 Notes: Introduction to Probability. Probability Rules. Independence and Conditional Probability. Bayes Theorem. Risk and Odds Ratio

4 Lecture 4 Notes: Introduction to Probability. Probability Rules. Independence and Conditional Probability. Bayes Theorem. Risk and Odds Ratio 4 Lecture 4 Notes: Introduction to Probability. Probability Rules. Independence and Conditional Probability. Bayes Theorem. Risk and Odds Ratio Wrong is right. Thelonious Monk 4.1 Three Definitions of

More information

AMS7: WEEK 2. CLASS 2

AMS7: WEEK 2. CLASS 2 AMS7: WEEK 2. CLASS 2 Introduction to Probability. Probability Rules. Independence and Conditional Probability. Bayes Theorem. Risk and Odds Ratio Friday April 10, 2015 Probability: Introduction Probability:

More information

Recap. The study of randomness and uncertainty Chances, odds, likelihood, expected, probably, on average,... PROBABILITY INFERENTIAL STATISTICS

Recap. The study of randomness and uncertainty Chances, odds, likelihood, expected, probably, on average,... PROBABILITY INFERENTIAL STATISTICS Recap. Probability (section 1.1) The study of randomness and uncertainty Chances, odds, likelihood, expected, probably, on average,... PROBABILITY Population Sample INFERENTIAL STATISTICS Today. Formulation

More information

Venn Diagrams; Probability Laws. Notes. Set Operations and Relations. Venn Diagram 2.1. Venn Diagrams; Probability Laws. Notes

Venn Diagrams; Probability Laws. Notes. Set Operations and Relations. Venn Diagram 2.1. Venn Diagrams; Probability Laws. Notes Lecture 2 s; Text: A Course in Probability by Weiss 2.4 STAT 225 Introduction to Probability Models January 8, 2014 s; Whitney Huang Purdue University 2.1 Agenda s; 1 2 2.2 Intersection: the intersection

More information

Tree and Venn Diagrams

Tree and Venn Diagrams OpenStax-CNX module: m46944 1 Tree and Venn Diagrams OpenStax College This work is produced by OpenStax-CNX and licensed under the Creative Commons Attribution License 3.0 Sometimes, when the probability

More information

13-5 Probabilities of Independent and Dependent Events

13-5 Probabilities of Independent and Dependent Events CCSS REASONING Determine whether the events are independent or dependent. Then find the probability. 6. In a game, you roll an even number on a die and then spin a spinner numbered 1 through 5 and get

More information

Probability the chance that an uncertain event will occur (always between 0 and 1)

Probability the chance that an uncertain event will occur (always between 0 and 1) Quantitative Methods 2013 1 Probability as a Numerical Measure of the Likelihood of Occurrence Probability the chance that an uncertain event will occur (always between 0 and 1) Increasing Likelihood of

More information

n N CHAPTER 1 Atoms Thermodynamics Molecules Statistical Thermodynamics (S.T.)

n N CHAPTER 1 Atoms Thermodynamics Molecules Statistical Thermodynamics (S.T.) CHAPTER 1 Atoms Thermodynamics Molecules Statistical Thermodynamics (S.T.) S.T. is the key to understanding driving forces. e.g., determines if a process proceeds spontaneously. Let s start with entropy

More information

Intro to Probability

Intro to Probability Intro to Probability February 26, 2019 Data Science CSCI 1951A Brown University Instructor: Ellie Pavlick HTAs: Wennie Zhang, Maulik Dang, Gurnaaz Kaur Content stolen largely from Dan Potter s 2016 version

More information

Chapter 01: Probability Theory (Cont d)

Chapter 01: Probability Theory (Cont d) Chapter 01: Probability Theory (Cont d) Section 1.5: Probabilities of Event Intersections Problem (01): When a company receives an order, there is a probability of 0.42 that its value is over $1000. If

More information

Statistics for Managers Using Microsoft Excel/SPSS Chapter 4 Basic Probability And Discrete Probability Distributions

Statistics for Managers Using Microsoft Excel/SPSS Chapter 4 Basic Probability And Discrete Probability Distributions Statistics for Managers Using Microsoft Excel/SPSS Chapter 4 Basic Probability And Discrete Probability Distributions 1999 Prentice-Hall, Inc. Chap. 4-1 Chapter Topics Basic Probability Concepts: Sample

More information

Chapter 2 PROBABILITY SAMPLE SPACE

Chapter 2 PROBABILITY SAMPLE SPACE Chapter 2 PROBABILITY Key words: Sample space, sample point, tree diagram, events, complement, union and intersection of an event, mutually exclusive events; Counting techniques: multiplication rule, permutation,

More information

Two events are mutually exclusive (disjoint) if they cannot occur at the same time. (OR)

Two events are mutually exclusive (disjoint) if they cannot occur at the same time. (OR) Two events are mutually exclusive (disjoint) if they cannot occur at the same time. (OR) Two events are independent if the occurrence of one does not change the probability of the other occurring. Probability

More information

Study Island Algebra 2 Post Test

Study Island Algebra 2 Post Test Study Island Algebra 2 Post Test 1. A two-sided fair coin has been tossed seven times. Three tosses have come up tails and four tosses have come up heads. What is the probability that the next toss will

More information

P ( A B ) = P ( A ) P ( B ) 1. The probability that a randomly selected student at Anytown College owns a bicycle is

P ( A B ) = P ( A ) P ( B ) 1. The probability that a randomly selected student at Anytown College owns a bicycle is STAT 400 UIUC Answers for.4 Stepanov Dalpiaz Events A and B are independent if and only if P ( B A ) = P ( B ) P ( A B ) = P ( A ) P ( A B ) = P ( A ) P ( B ) ote that if two events, A and B, are mutually

More information

1 Probability Theory. 1.1 Introduction

1 Probability Theory. 1.1 Introduction 1 Probability Theory Probability theory is used as a tool in statistics. It helps to evaluate the reliability of our conclusions about the population when we have only information about a sample. Probability

More information

Compound Events. The event E = E c (the complement of E) is the event consisting of those outcomes which are not in E.

Compound Events. The event E = E c (the complement of E) is the event consisting of those outcomes which are not in E. Compound Events Because we are using the framework of set theory to analyze probability, we can use unions, intersections and complements to break complex events into compositions of events for which it

More information

Please do NOT write in this box. Multiple Choice Total

Please do NOT write in this box. Multiple Choice Total Name: Instructor: ANSWERS Bullwinkle Math 1010, Exam I. October 14, 014 The Honor Code is in effect for this examination. All work is to be your own. Please turn off all cellphones and electronic devices.

More information

Example. What is the sample space for flipping a fair coin? Rolling a 6-sided die? Find the event E where E = {x x has exactly one head}

Example. What is the sample space for flipping a fair coin? Rolling a 6-sided die? Find the event E where E = {x x has exactly one head} Chapter 7 Notes 1 (c) Epstein, 2013 CHAPTER 7: PROBABILITY 7.1: Experiments, Sample Spaces and Events Chapter 7 Notes 2 (c) Epstein, 2013 What is the sample space for flipping a fair coin three times?

More information

Great Theoretical Ideas in Computer Science

Great Theoretical Ideas in Computer Science 15-251 Great Theoretical Ideas in Computer Science Probability Theory: Counting in Terms of Proportions Lecture 10 (September 27, 2007) Some Puzzles Teams A and B are equally good In any one game, each

More information

Statistics 251: Statistical Methods

Statistics 251: Statistical Methods Statistics 251: Statistical Methods Probability Module 3 2018 file:///volumes/users/r/renaes/documents/classes/lectures/251301/renae/markdown/master%20versions/module3.html#1 1/33 Terminology probability:

More information

Probability Long-Term Memory Review Review 1

Probability Long-Term Memory Review Review 1 Review. The formula for calculating theoretical probability of an event is What does the question mark represent? number of favorable outcomes P.? 2. True or False Experimental probability is always the

More information

Example. χ 2 = Continued on the next page. All cells

Example. χ 2 = Continued on the next page. All cells Section 11.1 Chi Square Statistic k Categories 1 st 2 nd 3 rd k th Total Observed Frequencies O 1 O 2 O 3 O k n Expected Frequencies E 1 E 2 E 3 E k n O 1 + O 2 + O 3 + + O k = n E 1 + E 2 + E 3 + + E

More information