Section 2.4 Bernoulli Trials

Size: px
Start display at page:

Download "Section 2.4 Bernoulli Trials"

Transcription

1 Section 2.4 Bernoulli Trials A bernoulli trial is a repeated experiment with the following properties: 1. There are two outcomes of each trial: success and failure. 2. The probability of success in each trial is the same. 3. The trials are independent of each other. 1. Which of the following experiments are bernoulli trials? (a) Rolling a fair die 20 times and, each time, observing if a 2 appears. (b) Selecting 4 cards from a standard deck of 52 cards without replacement and, each time, observing if an ace is drawn. (c) Assuming that there are 5 yellow and 7 white marbles in a jar. Choosing three marbles from the jar with replacement (put the marble back in the jar) and, each time, observing if a yellow marble is choosen. Random Variable A random variable is a rule that assigns a number to each outcome of a chance experiment. The random variable X in this section is associated with the outcomes of the bernoulli experiments. Computing Probabilities in a Bernoulli Experiment: Exactly x successes In a bernoulli experiment in which the probability of a success in any trial is p, the probability of exactly x successes in n independent trials is given by P (X = x) = C(n, x)p x (1 p) n x

2 Computing Probabilities in a Bernoulli Experiment: At Most x successes In a bernoulli experiment in which the probability of a success in any trial is p, the probability of at most x successes in n independent trials is given by P (X x) = P (X = 0) + P (X = 1) +... P (X = x) Bernoulli experiments are the same as Binomial experiments, and so we will use the Calculator function for the binomial distribution to compute the probabilities associated with bernoulli experiments. Calculator Steps: 2ND, VARS, scroll down to A or click ALPHA, MATH. Your screen should show binompdf(, this is for exactly x successes. For at most x successes, scoll down to B or click ALPHA, APPS. This time your screen should show binomcdf(. Here s the format for both: binompdf(n, p, x) or binomcdf(n, p, x). 2. It is estimated that one third of the general population has blood type A+. A sample of six people is selected at random. (Round answers to four decimal places.) (a) What is the probability that exactly two of them have blood type A+? (b) What is the probability that at most two of them have blood type A+? 2 Spring 2018, Maya Johnson

3 3. The probability that a DVD player produced by VCA Television is defective is estimated to be A sample of ten players is selected at random. (Round answers to four decimal places.) (a) What is the probability that the sample contains no defective units? (b) What is the probability that the sample contains at most two defective units? A Few Different Ways to use binomcdf 1. P (X x) = 1 binomcdf(n, p, x 1) at least x successes. 2. P (x 1 X x 2 ) = binomcdf(n, p, x 2 ) binomcdf(n, p, x 1 1) at least x 1 but at most x 2 successes. 3. P (x 1 < X x 2 ) = binomcdf(n, p, x 2 ) binomcdf(n, p, x 1 ) more than x 1 but at most x 2 successes. 4. P (x 1 X < x 2 ) = binomcdf(n, p, x 2 1) binomcdf(n, p, x 1 1) at least x 1 but fewer than x 2 successes. 5. P (x 1 < X < x 2 ) = binomcdf(n, p, x 2 1) binomcdf(n, p, x 1 ) more than x 1 but fewer than x 2 successes. 4. From experience, the manager of Kramer s Book Mart knows that 50% of the people who are browsing in the store will make a purchase. What is the probability that among ten people who are browsing in the store, at least four will make a purchase? (Round answer to four decimal places.) 3 Spring 2018, Maya Johnson

4 5. Suppose 30% of the restaurants in a certain part of a town are in violation of the health code. A health inspector randomly selects five of the restaurants for inspection. (Round answers to four decimal places.) (a) What is the probability that none of the restaurants are in violation of the health code? (b) What is the probability that one of the restaurants is in violation of the health code? (c) What is the probability that at least two of the restaurants are in violation of the health code? 6. The manager of Toy World knows that the probability an electronic game will be returned to the store is If 54 games are sold in a given week, determine the probabilities of the following events. (Round answers to four decimal places.) (a) No more than 12 games will be returned. (b) At least 8 games will be returned. (c) More than 5 games but fewer than 14 games will be returned. 4 Spring 2018, Maya Johnson

5 7. A coin is biased so that the probability of tossing a head is If this coin is tossed 54 times, determine the probabilities of the following events. (Round answers to four decimal places.) (a) The coin lands heads more than 21 times. (b) The coin lands heads fewer than 28 times. (c) The coin lands heads at least 20 times but at most 27 times. 8. A company finds that one out of four employees will be late to work on a given day. If this company has 40 employees, find the probabilities that the following number of people will get to work on time. (Round answers to four decimal places.) (a) Exactly 31 workers or exactly 35 workers. (b) At least 27 workers but fewer than 35 workers. (c) More than 25 workers but at most 37 workers. 5 Spring 2018, Maya Johnson

success and failure independent from one trial to the next?

success and failure independent from one trial to the next? , section 8.4 The Binomial Distribution Notes by Tim Pilachowski Definition of Bernoulli trials which make up a binomial experiment: The number of trials in an experiment is fixed. There are exactly two

More information

Name: Firas Rassoul-Agha

Name: Firas Rassoul-Agha Midterm 1 - Math 5010 - Spring 016 Name: Firas Rassoul-Agha Solve the following 4 problems. You have to clearly explain your solution. The answer carries no points. Only the work does. CALCULATORS ARE

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

MATH 250 / SPRING 2011 SAMPLE QUESTIONS / SET 3

MATH 250 / SPRING 2011 SAMPLE QUESTIONS / SET 3 MATH 250 / SPRING 2011 SAMPLE QUESTIONS / SET 3 1. A four engine plane can fly if at least two engines work. a) If the engines operate independently and each malfunctions with probability q, what is the

More information

Section 7.5 Conditional Probability and Independent Events

Section 7.5 Conditional Probability and Independent Events Section 75 Conditional Probability and Independent Events Conditional Probability of an Event If A and B are events in an experiment and P (A) 6= 0,thentheconditionalprobabilitythattheevent B will occur

More information

Math 227 Test 2 Ch5. Name

Math 227 Test 2 Ch5. Name Math 227 Test 2 Ch5 Name Find the mean of the given probability distribution. 1) In a certain town, 30% of adults have a college degree. The accompanying table describes the probability distribution for

More information

Random Variable. Discrete Random Variable. Continuous Random Variable. Discrete Random Variable. Discrete Probability Distribution

Random Variable. Discrete Random Variable. Continuous Random Variable. Discrete Random Variable. Discrete Probability Distribution Random Variable Theoretical Probability Distribution Random Variable Discrete Probability Distributions A variable that assumes a numerical description for the outcome of a random eperiment (by chance).

More information

Notes for Math 324, Part 17

Notes for Math 324, Part 17 126 Notes for Math 324, Part 17 Chapter 17 Common discrete distributions 17.1 Binomial Consider an experiment consisting by a series of trials. The only possible outcomes of the trials are success and

More information

Introductory Probability

Introductory Probability Introductory Probability Bernoulli Trials and Binomial Probability Distributions Dr. Nguyen nicholas.nguyen@uky.edu Department of Mathematics UK February 04, 2019 Agenda Bernoulli Trials and Probability

More information

Math 493 Final Exam December 01

Math 493 Final Exam December 01 Math 493 Final Exam December 01 NAME: ID NUMBER: Return your blue book to my office or the Math Department office by Noon on Tuesday 11 th. On all parts after the first show enough work in your exam booklet

More information

Exam 3 Review (Sections Covered: , )

Exam 3 Review (Sections Covered: , ) 19 Exam Review (Secions Covered: 776 8184) 1 Adieisloadedandihasbeendeerminedhaheprobabiliydisribuionassociaedwih he experimen of rolling he die and observing which number falls uppermos is given by he

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

Probability Experiments, Trials, Outcomes, Sample Spaces Example 1 Example 2

Probability Experiments, Trials, Outcomes, Sample Spaces Example 1 Example 2 Probability Probability is the study of uncertain events or outcomes. Games of chance that involve rolling dice or dealing cards are one obvious area of application. However, probability models underlie

More information

Each trial has only two possible outcomes success and failure. The possible outcomes are exactly the same for each trial.

Each trial has only two possible outcomes success and failure. The possible outcomes are exactly the same for each trial. Section 8.6: Bernoulli Experiments and Binomial Distribution We have already learned how to solve problems such as if a person randomly guesses the answers to 10 multiple choice questions, what is the

More information

Section 7.1 Experiments, Sample Spaces, and Events

Section 7.1 Experiments, Sample Spaces, and Events Section 7.1 Experiments, Sample Spaces, and Events Experiments An experiment is an activity with observable results. 1. Which of the follow are experiments? (a) Going into a room and turning on a light.

More information

Chapter 3 Probability Distribution

Chapter 3 Probability Distribution Chapter 3 Probability Distribution Probability Distributions A probability function is a function which assigns probabilities to the values of a random variable. Individual probability values may be denoted

More information

8 Probability. An event occurs if, when the experiment is performed, the outcome is in that event.

8 Probability. An event occurs if, when the experiment is performed, the outcome is in that event. 8 Probability When an experiment is performed, an outcome is observed. A set of possible outcomes is an event. The sample space for the experiment is the set of all possible outcomes. An experiment must

More information

Answers Only VI- Counting Principles; Further Probability Topics

Answers Only VI- Counting Principles; Further Probability Topics Answers Only VI- Counting Principles; Further Probability Topics 1) If you are dealt 3 cards from a shuffled deck of 52 cards, find the probability that all 3 cards are clubs. (Type a fraction. Simplify

More information

Chapter. Probability

Chapter. Probability Chapter 3 Probability Section 3.1 Basic Concepts of Probability Section 3.1 Objectives Identify the sample space of a probability experiment Identify simple events Use the Fundamental Counting Principle

More information

Some Special Discrete Distributions

Some Special Discrete Distributions Mathematics Department De La Salle University Manila February 6, 2017 Some Discrete Distributions Often, the observations generated by different statistical experiments have the same general type of behaviour.

More information

Probability Rules. MATH 130, Elements of Statistics I. J. Robert Buchanan. Fall Department of Mathematics

Probability Rules. MATH 130, Elements of Statistics I. J. Robert Buchanan. Fall Department of Mathematics Probability Rules MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2018 Introduction Probability is a measure of the likelihood of the occurrence of a certain behavior

More information

What is Probability? Probability. Sample Spaces and Events. Simple Event

What is Probability? Probability. Sample Spaces and Events. Simple Event What is Probability? Probability Peter Lo Probability is the numerical measure of likelihood that the event will occur. Simple Event Joint Event Compound Event Lies between 0 & 1 Sum of events is 1 1.5

More information

CHAPTER 3 PROBABILITY: EVENTS AND PROBABILITIES

CHAPTER 3 PROBABILITY: EVENTS AND PROBABILITIES CHAPTER 3 PROBABILITY: EVENTS AND PROBABILITIES PROBABILITY: A probability is a number between 0 and 1, inclusive, that states the long-run relative frequency, likelihood, or chance that an outcome will

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

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

Math 511 Exam #1. Show All Work No Calculators

Math 511 Exam #1. Show All Work No Calculators Math 511 Exam #1 Show All Work No Calculators 1. Suppose that A and B are events in a sample space S and that P(A) = 0.4 and P(B) = 0.6 and P(A B) = 0.3. Suppose too that B, C, and D are mutually independent

More information

STA 2023 EXAM-2 Practice Problems. Ven Mudunuru. From Chapters 4, 5, & Partly 6. With SOLUTIONS

STA 2023 EXAM-2 Practice Problems. Ven Mudunuru. From Chapters 4, 5, & Partly 6. With SOLUTIONS STA 2023 EXAM-2 Practice Problems From Chapters 4, 5, & Partly 6 With SOLUTIONS Mudunuru, Venkateswara Rao STA 2023 Spring 2016 1 1. A committee of 5 persons is to be formed from 6 men and 4 women. What

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

DISCRETE VARIABLE PROBLEMS ONLY

DISCRETE VARIABLE PROBLEMS ONLY DISCRETE VARIABLE PROBLEMS ONLY. A biased die with four faces is used in a game. A player pays 0 counters to roll the die. The table below shows the possible scores on the die, the probability of each

More information

Week 6, 9/24/12-9/28/12, Notes: Bernoulli, Binomial, Hypergeometric, and Poisson Random Variables

Week 6, 9/24/12-9/28/12, Notes: Bernoulli, Binomial, Hypergeometric, and Poisson Random Variables Week 6, 9/24/12-9/28/12, Notes: Bernoulli, Binomial, Hypergeometric, and Poisson Random Variables 1 Monday 9/24/12 on Bernoulli and Binomial R.V.s We are now discussing discrete random variables that have

More information

Exam III Review Math-132 (Sections 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 8.1, 8.2, 8.3)

Exam III Review Math-132 (Sections 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 8.1, 8.2, 8.3) 1 Exam III Review Math-132 (Sections 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 8.1, 8.2, 8.3) On this exam, questions may come from any of the following topic areas: - Union and intersection of sets - Complement of

More information

Discrete Distributions

Discrete Distributions A simplest example of random experiment is a coin-tossing, formally called Bernoulli trial. It happens to be the case that many useful distributions are built upon this simplest form of experiment, whose

More information

Section 7.2 Definition of Probability

Section 7.2 Definition of Probability Section 7.2 Definition of Probability Question: Suppose we have an experiment that consists of flipping a fair 2-sided coin and observing if the coin lands on heads or tails? From section 7.1 we should

More information

Geometric Distribution The characteristics of a geometric experiment are: 1. There are one or more Bernoulli trials with all failures except the last

Geometric Distribution The characteristics of a geometric experiment are: 1. There are one or more Bernoulli trials with all failures except the last Geometric Distribution The characteristics of a geometric experiment are: 1. There are one or more Bernoulli trials with all failures except the last one, which is a success. In other words, you keep repeating

More information

REPEATED TRIALS. p(e 1 ) p(e 2 )... p(e k )

REPEATED TRIALS. p(e 1 ) p(e 2 )... p(e k ) REPEATED TRIALS We first note a basic fact about probability and counting. Suppose E 1 and E 2 are independent events. For example, you could think of E 1 as the event of tossing two dice and getting a

More information

Question Paper Code : AEC11T03

Question Paper Code : AEC11T03 Hall Ticket No Question Paper Code : AEC11T03 VARDHAMAN COLLEGE OF ENGINEERING (AUTONOMOUS) Affiliated to JNTUH, Hyderabad Four Year B Tech III Semester Tutorial Question Bank 2013-14 (Regulations: VCE-R11)

More information

Discrete Random Variable Practice

Discrete Random Variable Practice IB Math High Level Year Discrete Probability Distributions - MarkScheme Discrete Random Variable Practice. A biased die with four faces is used in a game. A player pays 0 counters to roll the die. The

More information

MA 250 Probability and Statistics. Nazar Khan PUCIT Lecture 15

MA 250 Probability and Statistics. Nazar Khan PUCIT Lecture 15 MA 250 Probability and Statistics Nazar Khan PUCIT Lecture 15 RANDOM VARIABLES Random Variables Random variables come in 2 types 1. Discrete set of outputs is real valued, countable set 2. Continuous set

More information

MTH 201 Applied Mathematics Sample Final Exam Questions. 1. The augmented matrix of a system of equations (in two variables) is:

MTH 201 Applied Mathematics Sample Final Exam Questions. 1. The augmented matrix of a system of equations (in two variables) is: MTH 201 Applied Mathematics Sample Final Exam Questions 1. The augmented matrix of a system of equations (in two variables) is: 2 1 6 4 2 12 Which of the following is true about the system of equations?

More information

Probability Distributions

Probability Distributions EXAMPLE: Consider rolling a fair die twice. Probability Distributions Random Variables S = {(i, j : i, j {,...,6}} Suppose we are interested in computing the sum, i.e. we have placed a bet at a craps table.

More information

an event with one outcome is called a simple event.

an event with one outcome is called a simple event. Ch5Probability Probability is a measure of the likelihood of a random phenomenon or chance behavior. Probability describes the long-term proportion with which a certain outcome will occur in situations

More information

Computations - Show all your work. (30 pts)

Computations - Show all your work. (30 pts) Math 1012 Final Name: Computations - Show all your work. (30 pts) 1. Fractions. a. 1 7 + 1 5 b. 12 5 5 9 c. 6 8 2 16 d. 1 6 + 2 5 + 3 4 2.a Powers of ten. i. 10 3 10 2 ii. 10 2 10 6 iii. 10 0 iv. (10 5

More information

STA 2023 EXAM-2 Practice Problems From Chapters 4, 5, & Partly 6. With SOLUTIONS

STA 2023 EXAM-2 Practice Problems From Chapters 4, 5, & Partly 6. With SOLUTIONS STA 2023 EXAM-2 Practice Problems From Chapters 4, 5, & Partly 6 With SOLUTIONS Mudunuru Venkateswara Rao, Ph.D. STA 2023 Fall 2016 Venkat Mu ALL THE CONTENT IN THESE SOLUTIONS PRESENTED IN BLUE AND BLACK

More information

Expectations. Definition Let X be a discrete rv with set of possible values D and pmf p(x). The expected value or mean value of X, denoted by E(X ) or

Expectations. Definition Let X be a discrete rv with set of possible values D and pmf p(x). The expected value or mean value of X, denoted by E(X ) or Expectations Expectations Definition Let X be a discrete rv with set of possible values D and pmf p(x). The expected value or mean value of X, denoted by E(X ) or µ X, is E(X ) = µ X = x D x p(x) Expectations

More information

Chapter 6. Probability

Chapter 6. Probability Chapter 6 robability Suppose two six-sided die is rolled and they both land on sixes. Or a coin is flipped and it lands on heads. Or record the color of the next 20 cars to pass an intersection. These

More information

4.2 Probability Models

4.2 Probability Models 4.2 Probability Models Ulrich Hoensch Tuesday, February 19, 2013 Sample Spaces Examples 1. When tossing a coin, the sample space is S = {H, T }, where H = heads, T = tails. 2. When randomly selecting a

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

UNIVERSITY OF CALIFORNIA, BERKELEY

UNIVERSITY OF CALIFORNIA, BERKELEY UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF STATISTICS STAT 34: Concepts of Probability Spring 24 Instructor: Antar Bandyopadhyay Solution to the Midterm Examination. A point X, Y is randomly selected

More information

Conditional Probability

Conditional Probability Conditional Probability Idea have performed a chance experiment but don t know the outcome (ω), but have some partial information (event A) about ω. Question: given this partial information what s the

More information

Conditional Probability (cont'd)

Conditional Probability (cont'd) Conditional Probability (cont'd) April 26, 2006 Conditional Probability (cont'd) Midterm Problems In a ten-question true-false exam, nd the probability that a student get a grade of 70 percent or better

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

Section F Ratio and proportion

Section F Ratio and proportion Section F Ratio and proportion Ratio is a way of comparing two or more groups. For example, if something is split in a ratio 3 : 5 there are three parts of the first thing to every five parts of the second

More information

Lecture Lecture 5

Lecture Lecture 5 Lecture 4 --- Lecture 5 A. Basic Concepts (4.1-4.2) 1. Experiment: A process of observing a phenomenon that has variation in its outcome. Examples: (E1). Rolling a die, (E2). Drawing a card form a shuffled

More information

Chapter 3: Probability 3.1: Basic Concepts of Probability

Chapter 3: Probability 3.1: Basic Concepts of Probability Chapter 3: Probability 3.1: Basic Concepts of Probability Objectives Identify the sample space of a probability experiment and a simple event Use the Fundamental Counting Principle Distinguish classical

More information

Tutorial 3 - Discrete Probability Distributions

Tutorial 3 - Discrete Probability Distributions Tutorial 3 - Discrete Probability Distributions 1. If X ~ Bin(6, ), find (a) P(X = 4) (b) P(X 2) 2. If X ~ Bin(8, 0.4), find (a) P(X = 2) (b) P(X = 0) (c)p(x > 6) 3. The probability that a pen drawn at

More information

Exam 2 Review (Sections Covered: 3.1, 3.3, , 7.1) Solutro. 1. Write a system of linear inequalities that describes the shaded region.

Exam 2 Review (Sections Covered: 3.1, 3.3, , 7.1) Solutro. 1. Write a system of linear inequalities that describes the shaded region. Exam 2 Review (Sections Covered: 31 33 6164 71) Solutro 1 Write a system of linear inequalities that describes the shaded region :) 5x +2y 30 x +2y " 2) 12 x : 0 y Z 0 : Line as 0 TO ± 30 True Line (2)

More information

Example. If 4 tickets are drawn with replacement from ,

Example. If 4 tickets are drawn with replacement from , Example. If 4 tickets are drawn with replacement from 1 2 2 4 6, what are the chances that we observe exactly two 2 s? Exactly two 2 s in a sequence of four draws can occur in many ways. For example, (

More information

Chapter 11 Introduction to probability

Chapter 11 Introduction to probability MB Qld- 8 Chapter Exercise A Informal description of chance a Double digits from 0 to 0 Probable b Only girls out of 30 Unlikely c No green marbles Impossible d Half the numbers are odd Fifty-fifty 2 a

More information

PLEASE MARK YOUR ANSWERS WITH AN X, not a circle! 1. (a) (b) (c) (d) (e) 2. (a) (b) (c) (d) (e) (a) (b) (c) (d) (e) 4. (a) (b) (c) (d) (e)...

PLEASE MARK YOUR ANSWERS WITH AN X, not a circle! 1. (a) (b) (c) (d) (e) 2. (a) (b) (c) (d) (e) (a) (b) (c) (d) (e) 4. (a) (b) (c) (d) (e)... Math 020, Exam II October, 206 The Honor Code is in effect for this examination. All work is to be your own. You may use a calculator. The exam lasts for hour 5 minutes. Be sure that your name is on every

More information

(A) Incorrect! A parameter is a number that describes the population. (C) Incorrect! In a Random Sample, not just a sample.

(A) Incorrect! A parameter is a number that describes the population. (C) Incorrect! In a Random Sample, not just a sample. AP Statistics - Problem Drill 15: Sampling Distributions No. 1 of 10 Instructions: (1) Read the problem statement and answer choices carefully (2) Work the problems on paper 1. Which one of the following

More information

Math 447. Introduction to Probability and Statistics I. Fall 1998.

Math 447. Introduction to Probability and Statistics I. Fall 1998. Math 447. Introduction to Probability and Statistics I. Fall 1998. Schedule: M. W. F.: 08:00-09:30 am. SW 323 Textbook: Introduction to Mathematical Statistics by R. V. Hogg and A. T. Craig, 1995, Fifth

More information

6.041/6.431 Spring 2009 Quiz 1 Wednesday, March 11, 7:30-9:30 PM. SOLUTIONS

6.041/6.431 Spring 2009 Quiz 1 Wednesday, March 11, 7:30-9:30 PM. SOLUTIONS 6.0/6.3 Spring 009 Quiz Wednesday, March, 7:30-9:30 PM. SOLUTIONS Name: Recitation Instructor: Question Part Score Out of 0 all 0 a 5 b c 5 d 5 e 5 f 5 3 a b c d 5 e 5 f 5 g 5 h 5 Total 00 Write your solutions

More information

Introduction to Probability, Fall 2013

Introduction to Probability, Fall 2013 Introduction to Probability, Fall 2013 Math 30530 Section 01 Homework 4 Solutions 1. Chapter 2, Problem 1 2. Chapter 2, Problem 2 3. Chapter 2, Problem 3 4. Chapter 2, Problem 5 5. Chapter 2, Problem 6

More information

STAT Chapter 3: Probability

STAT Chapter 3: Probability Basic Definitions STAT 515 --- Chapter 3: Probability Experiment: A process which leads to a single outcome (called a sample point) that cannot be predicted with certainty. Sample Space (of an experiment):

More information

ELEG 3143 Probability & Stochastic Process Ch. 2 Discrete Random Variables

ELEG 3143 Probability & Stochastic Process Ch. 2 Discrete Random Variables Department of Electrical Engineering University of Arkansas ELEG 3143 Probability & Stochastic Process Ch. 2 Discrete Random Variables Dr. Jingxian Wu wuj@uark.edu OUTLINE 2 Random Variable Discrete Random

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

Total. Name: Student ID: CSE 21A. Midterm #2. February 28, 2013

Total. Name: Student ID: CSE 21A. Midterm #2. February 28, 2013 Name: Student ID: CSE 21A Midterm #2 February 28, 2013 There are 6 problems. The number of points a problem is worth is shown next to the problem. Show your work (even on multiple choice questions)! Also,

More information

( ) P A B : Probability of A given B. Probability that A happens

( ) P A B : Probability of A given B. Probability that A happens A B A or B One or the other or both occurs At least one of A or B occurs Probability Review A B A and B Both A and B occur ( ) P A B : Probability of A given B. Probability that A happens given that B

More information

1. If X has density. cx 3 e x ), 0 x < 0, otherwise. Find the value of c that makes f a probability density. f(x) =

1. If X has density. cx 3 e x ), 0 x < 0, otherwise. Find the value of c that makes f a probability density. f(x) = 1. If X has density f(x) = { cx 3 e x ), 0 x < 0, otherwise. Find the value of c that makes f a probability density. 2. Let X have density f(x) = { xe x, 0 < x < 0, otherwise. (a) Find P (X > 2). (b) Find

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

Math 218 Supplemental Instruction Spring 2008 Final Review Part A

Math 218 Supplemental Instruction Spring 2008 Final Review Part A Spring 2008 Final Review Part A SI leaders: Mario Panak, Jackie Hu, Christina Tasooji Chapters 3, 4, and 5 Topics Covered: General probability (probability laws, conditional, joint probabilities, independence)

More information

Exam III #1 Solutions

Exam III #1 Solutions Department of Mathematics University of Notre Dame Math 10120 Finite Math Fall 2017 Name: Instructors: Basit & Migliore Exam III #1 Solutions November 14, 2017 This exam is in two parts on 11 pages and

More information

Solutionbank S1 Edexcel AS and A Level Modular Mathematics

Solutionbank S1 Edexcel AS and A Level Modular Mathematics Heinemann Solutionbank: Statistics S Page of Solutionbank S Exercise A, Question Write down whether or not each of the following is a discrete random variable. Give a reason for your answer. a The average

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

EXAM. Exam #1. Math 3342 Summer II, July 21, 2000 ANSWERS

EXAM. Exam #1. Math 3342 Summer II, July 21, 2000 ANSWERS EXAM Exam # Math 3342 Summer II, 2 July 2, 2 ANSWERS i pts. Problem. Consider the following data: 7, 8, 9, 2,, 7, 2, 3. Find the first quartile, the median, and the third quartile. Make a box and whisker

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

Senior Math Circles November 19, 2008 Probability II

Senior Math Circles November 19, 2008 Probability II University of Waterloo Faculty of Mathematics Centre for Education in Mathematics and Computing Senior Math Circles November 9, 2008 Probability II Probability Counting There are many situations where

More information

Module 8 Probability

Module 8 Probability Module 8 Probability Probability is an important part of modern mathematics and modern life, since so many things involve randomness. The ClassWiz is helpful for calculating probabilities, especially those

More information

MTH302 Quiz # 4. Solved By When a coin is tossed once, the probability of getting head is. Select correct option:

MTH302 Quiz # 4. Solved By When a coin is tossed once, the probability of getting head is. Select correct option: MTH302 Quiz # 4 Solved By konenuchiha@gmail.com When a coin is tossed once, the probability of getting head is. 0.55 0.52 0.50 (1/2) 0.51 Suppose the slope of regression line is 20 and the intercept is

More information

DSST Principles of Statistics

DSST Principles of Statistics DSST Principles of Statistics Time 10 Minutes 98 Questions Each incomplete statement is followed by four suggested completions. Select the one that is best in each case. 1. Which of the following variables

More information

Section 3 2 Probability Genetics Answers

Section 3 2 Probability Genetics Answers We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with section 3 2 probability

More information

(a) Fill in the missing probabilities in the table. (b) Calculate P(F G). (c) Calculate P(E c ). (d) Is this a uniform sample space?

(a) Fill in the missing probabilities in the table. (b) Calculate P(F G). (c) Calculate P(E c ). (d) Is this a uniform sample space? Math 166 Exam 1 Review Sections L.1-L.2, 1.1-1.7 Note: This review is more heavily weighted on the new material this week: Sections 1.5-1.7. For more practice problems on previous material, take a look

More information

Name: Exam 2 Solutions. March 13, 2017

Name: Exam 2 Solutions. March 13, 2017 Department of Mathematics University of Notre Dame Math 00 Finite Math Spring 07 Name: Instructors: Conant/Galvin Exam Solutions March, 07 This exam is in two parts on pages and contains problems worth

More information

Binomial and Poisson Probability Distributions

Binomial and Poisson Probability Distributions Binomial and Poisson Probability Distributions Esra Akdeniz March 3, 2016 Bernoulli Random Variable Any random variable whose only possible values are 0 or 1 is called a Bernoulli random variable. What

More information

Exam 2 Review Math 118 Sections 1 and 2

Exam 2 Review Math 118 Sections 1 and 2 Exam 2 Review Math 118 Sections 1 and 2 This exam will cover sections 2.4, 2.5, 3.1-3.3, 4.1-4.3 and 5.1-5.2 of the textbook. No books, notes, calculators or other aids are allowed on this exam. There

More information

1 of 6 7/16/2009 6:31 AM Virtual Laboratories > 11. Bernoulli Trials > 1 2 3 4 5 6 1. Introduction Basic Theory The Bernoulli trials process, named after James Bernoulli, is one of the simplest yet most

More information

1. Discrete Distributions

1. Discrete Distributions Virtual Laboratories > 2. Distributions > 1 2 3 4 5 6 7 8 1. Discrete Distributions Basic Theory As usual, we start with a random experiment with probability measure P on an underlying sample space Ω.

More information

Chapter 3 Probability Distributions and Statistics Section 3.1 Random Variables and Histograms

Chapter 3 Probability Distributions and Statistics Section 3.1 Random Variables and Histograms Math 166 (c)2013 Epstein Chapter 3 Page 1 Chapter 3 Probability Distributions and Statistics Section 3.1 Random Variables and Histograms The value of the result of the probability experiment is called

More information

Discrete Distributions

Discrete Distributions Discrete Distributions Applications of the Binomial Distribution A manufacturing plant labels items as either defective or acceptable A firm bidding for contracts will either get a contract or not A marketing

More information

The Central Limit Theorem

The Central Limit Theorem The Central Limit Theorem Suppose n tickets are drawn at random with replacement from a box of numbered tickets. The central limit theorem says that when the probability histogram for the sum of the draws

More information

Principles of Mathematics 12

Principles of Mathematics 12 Principles of Mathematics 12 Examination Booklet Sample 2007/08 Form A DO NOT OPEN ANY EXAMINATION MATERIALS UNTIL INSTRUCTED TO DO SO. FOR FURTHER INSTRUCTIONS REFER TO THE RESPONSE BOOKLET. Contents:

More information

, x {1, 2, k}, where k > 0. Find E(X). (2) (Total 7 marks)

, x {1, 2, k}, where k > 0. Find E(X). (2) (Total 7 marks) 1.) The probability distribution of a discrete random variable X is given by 2 x P(X = x) = 14, x {1, 2, k}, where k > 0. Write down P(X = 2). Show that k = 3. (1) Find E(X). (Total 7 marks) 2.) In a group

More information

Probability and Sample space

Probability and Sample space Probability and Sample space We call a phenomenon random if individual outcomes are uncertain but there is a regular distribution of outcomes in a large number of repetitions. The probability of any outcome

More information

Elementary Discrete Probability

Elementary Discrete Probability Elementary Discrete Probability MATH 472 Financial Mathematics J Robert Buchanan 2018 Objectives In this lesson we will learn: the terminology of elementary probability, elementary rules of probability,

More information

Counting principles, including permutations and combinations.

Counting principles, including permutations and combinations. 1 Counting principles, including permutations and combinations. The binomial theorem: expansion of a + b n, n ε N. THE PRODUCT RULE If there are m different ways of performing an operation and for each

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

Introduction to probability

Introduction to probability Introduction to probability 4.1 The Basics of Probability Probability The chance that a particular event will occur The probability value will be in the range 0 to 1 Experiment A process that produces

More information

BINOMIAL DISTRIBUTION

BINOMIAL DISTRIBUTION BINOMIAL DISTRIBUTION The binomial distribution is a particular type of discrete pmf. It describes random variables which satisfy the following conditions: 1 You perform n identical experiments (called

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

Discrete Probability Distributions

Discrete Probability Distributions Discrete Probability Distributions Data Science: Jordan Boyd-Graber University of Maryland JANUARY 18, 2018 Data Science: Jordan Boyd-Graber UMD Discrete Probability Distributions 1 / 1 Refresher: Random

More information