PLEASE MARK YOUR ANSWERS WITH AN X, not a circle!

Size: px
Start display at page:

Download "PLEASE MARK YOUR ANSWERS WITH AN X, not a circle!"

Transcription

1 Name: Version # nstructor: Annette McP Math 020 Exam 3 Nov. 3, 208. The Honor Code is in e ect for this examination. All work is to be your own. Please turn o all cellphones and electronic devices. Calculators are allowed. The exam lasts for hour and minutes. Be sure that your name and your instructor s name are on the front page of your exam. Be sure that you have all 2 pages of the test. PLEASE MARK YOUR ANSWERS WTH AN X, not a circle!. ( ) (b) (c) (d) (e) 2 ( ) (b) (c) (d) (e) 3. ( ) (b) (c) (d) (e) 4. ( ) (b) (c) (d) (e). ( ) (b) (c) (d) (e). ( ) (b) (c) (d) (e) 7. ( ) (b) (c) (d) (e) 8. ( ) (b) (c) (d) (e) 9. ( ) (b) (c) (d) (e) 0. ( ) (b) (c) (d) (e) Please do NOT write in this box. Multiple Choice Total

2 Name: nstructor: Math 020 Exam 3 Nov. 3, 208. The Honor Code is in e ect for this examination. All work is to be your own. Please turn o all cellphones and electronic devices. Calculators are allowed. The exam lasts for hour and minutes. Be sure that your name and your instructor s name are on the front page of your exam. Be sure that you have all 2 pages of the test. PLEASE MARK YOUR ANSWERS WTH AN X, not a circle!. (a) (b) (c) (d) (e) 2 (a) (b) (c) (d) (e) 3. (a) (b) (c) (d) (e) 4. (a) (b) (c) (d) (e). (a) (b) (c) (d) (e). (a) (b) (c) (d) (e) 7. (a) (b) (c) (d) (e) 8. (a) (b) (c) (d) (e) 9. (a) (b) (c) (d) (e) 0. (a) (b) (c) (d) (e) Please do NOT write in this box. Multiple Choice Total

3 2. nitials: Multiple Choice.(pts) The number of pets per household was recorded for a random sample of 40 households in the South Bend area. The results for the sample are shown in the relative frequency distribution below. How many of the households had at least three pets? (a) (b) 8 (c) 2 (d) 20 (e) 40 x 3 pets d pets Co 340 pets pets a 2 0. to (pts) The average of the following data was x =3. What is the value of the observation a? a, 0,,,, 3, 3, 3, 3, X Ato ti t t (a) 0 (b) (c) 2 (d) 3 (e) 0 3 i e at 20 To 3 a

4 3. nitials: 3.(pts) The Temperature readings at Noon in the town of Ballybrack for a random sample of 30 days are given in the following table: 7 30 Temerature Frequency 0 SE Seem x ETH ex E 2 xf 22 2 E.EE 9 ggs rsefeg The average temperature in the sample is x = (there is no need to check this). What is the sample standard deviation? (a) s = X r (b) s = r 08 9 (c) s = r (d) s = r (e) s =0 4.(pts) A box contains 4 red marbles and 3 blue marbles. A sample of two marbles is drawn at random from the box. Let X denote the number of blue marbles in the sample. Which of the following gives the probability distribution for the random variable X? x (a) (c) (e) X P(X) 0 2/7 4/7 2 /7 X P(X) 0 /7 /7 2 /7 X P(X) 4/7 2 3/7 r (b) (d) X P(X) 0 2/7 3/7 2 2/7 X P(X) 3/7 2 4/7 33 Exp Draw sample of SZE 2 X A B in sample Possible valuesof X O l 23 Plx o CCG 2 2 PCx P in aiiiibj CC4 43, 4 7 EEL PC 2 P all B CC3 CC7,2 L 7 P Call R

5 4. nitials:.(pts) A carnival game has the following rules: The player pays $ to play the game. The player then draws a card from a well shu ed standard deck of 2 cards. f the card drawn is not a heart, the game is over and the player loses. f the card drawn is a heart, the player flips a coin. f the player gets a tail on the coin, the game is over and the player loses. f the player gets a head on the coin, the player wins and receives $2 from the game attendant. Let X be the (net) earnings for the player in this game. What is the expected value of X? (A tree diagram might help). (a) -$.87 (b) -$3.2 (c) $2 (d) $20 (e) - $2..(pts) A fair die is tossed 0 times. What is the probability of getting at most eight sixes? (a) - " (b) C(0, 8) (c) C(0, 8) (d) C(0, 9) (e) 8 C(0, 9) C(0, 0) C(0, 9) 9 + C(0, 0) # + C(0, 0) 0 FCx X sixes has binomial dust nao 4 4 of P 8 P x 8 P x 9 tpcx iob Clio 9 f 9g Cao lo ft is

6 . nitials: 7.(pts) f Z is a standard normal random variable, what is P ( 0. apple Z apple 0.). Note You will find tables for the standard normal distribution at the end of the exam. f you use a calculator, please choose the answer below that is closest to your answer. (a) (b) 0.9 (c) (d) 0.82 (e) 0.7 From tables PC 0. E Z e oust Alas Al a (pts) Let T denote the average daily surface temperature of planet rt. The variable T is normally distributed with mean µ =7. degrees Fahrenheit and standard deviation = 0.4. What is the probability that tomorrow s average surface temperature for planet rt will be above 8.32 degrees Fahrenheit? (a) (b) (c) 0.79 x (d) (e) PCT 8.32 P TE 8.32 L p z e P Cz z wherez is standard normal Plz e 2 a L A FROM Tables

7 . nitials: 9.(pts) The feasible set of the inequalities shown below corresponds to the shaded region in one of the following pictures, which one? x 0 x apple 8 y 0 y apple 0 3x + 4y apple 24 2x y apple i i (a) v f is (b) F S 4 24 (c) (d) (e) None of the above 0.(pts) Find the intersection of the two lines 3x 2y =4 x + y =3 Hzy 4 Sx (a) (2, ) (b) (2, 0) (c) (3, ) (d) (, 3) (e) (, 2) set y's equal 3 2 D 4 3 x 3 4 2x Ex co x 3E.T y 3 tjsubskct.at

8 7. nitials: Partial Credit You may use symbols such as C(n, k), P (n, k) and factorials in your final answers for partial credit questions..(2pts) The Orange Electronics Company company produces jphones. Two percent of the jphones they produce are defective. D defective P D 0.02 (a) The jphones are produced at the Orange Company s manufacturing plant, and are sent in boxes of 40 to the jphone retail stores. A random selection of 40 jphones is packed in a box for shipment. What is the probability that the box will contain less than 3 defective jphones? X D in sampleof 40 X has binom distribution n PX 3 Plx o t PCx DtPCx z o g g of 40 o t C 40,2 o (b) Each customer has the option of buying a one year warranty with their new jphone. The warranty costs $00 and covers the cost of repairs in the first year. n their first year, 9% of new jphones need no repairs, 2% require repairs costing $300, and 3% require repairs costing $00. What is the average profit per warranty sold for the jphone company? Hint: The expected value may help. X Profit on warranty sold Possible Values of X are 00 No repairs necess 200 repairs costing 300 recess news is 9 E f9l average profit forcompany Per warranty sold

9 8. nitials: 2.(2pts) The lifetime of the Winged Twitchycephalope is normally distributed with mean 20 years and standard deviation 3 years. Let X denote the lifetime of a Winged Twitchycephalope chosen at random from the population. (i) The graphs below represent areas under the standard normal distribution, with mean zero and standard deviation. Which of the shaded areas shown below equals P (X apple 23), where X is the random variable described above. Z PGE 23 P ZE Pfizer (a) (b) Z Z (c) (d) Z Z (ii) Calculate P (X apple 23), where X is the random variable described above. PX E 237 Plz All 843 front Table (iii) n a random sample of 00 Winged Twitchycephalopes, how many would you expect to live to an age greater than 23 years? PCX 23 l Plex 3 L 8h3 287 Approx Wcriged Twitchy cephalifes in ar sample of 00 would lie to an age 323 yrs

10 9. nitials: 3.(2pts) At a fairground game stand, you pay $2 to play. You then roll a fair six sided die until you get a number less than or until you have rolled the die 3 times (whichever comes first). When you are finished rolling the die, the game attendant gives you $2 for every roll of the die you have made. Let X denote the (net) earnings for the player for one play of this game. (a) Find the probability distribution for the random variable X. i X i i Pr(X) Et t O EcxF (b) What is E(X) (theexpectedvalueofx) fortheprobabilitydistributionyoufoundin Part (a)? (c) f you played this game 0 times, how much would you expect to win? Expect to win g

11 0. nitials: 4.(2pts) Lauren has recorded her rowing time (in seconds) for 00 meters over a period of 20 days. The results are shown below. (a), 2, 3,, 2, 0, 3,, 2, 3,, 0, 2, 3,, 4, 2, 3, 0, 2 What was the relative frequency of the observation 2 in Lauren s data? N 2O Freq Dist o's freq of 0 is (b) What was the mean time ( x) inlauren sdata. s t 2 t.3 t fmizaw lt (c) What is the median time for Lauren s data? n 20 observations MEDAN T median average of middle two a a doth and ofs ordered Data t Authobs lodobs Med 2 2

12 . nitials:.(2pts) You will be awarded these two points if you write your name in CAPTALS and you mark your answers on the front page with an X (not an O). You may also use this page for ROUGH WORK i E T.E.no ae mmmm

13 2. nitials: Areas under the Standard Normal Curve Area = A(z) = P(Z z) 0 z Z z A(z) z A(z) z A(z) z A(z) z A(z)

Chapter 3: Probability Distributions and Statistics

Chapter 3: Probability Distributions and Statistics Chapter 3: Probability Distributions and Statistics Section 3.-3.3 3. Random Variables and Histograms A is a rule that assigns precisely one real number to each outcome of an experiment. We usually denote

More information

Fall 2015 Math 141:505 Exam 3 Form A

Fall 2015 Math 141:505 Exam 3 Form A Fall 205 Math 4:505 Exam 3 Form A Last Name: First Name: Exam Seat #: UIN: On my honor, as an Aggie, I have neither given nor received unauthorized aid on this academic work Signature: INSTRUCTIONS Part

More information

Learning Goals: * Determining the expected value from a probability distribution. * Applying the expected value formula to solve problems.

Learning Goals: * Determining the expected value from a probability distribution. * Applying the expected value formula to solve problems. Learning Goals: * Determining the expected value from a probability distribution. * Applying the expected value formula to solve problems. The following are marks from assignments and tests in a math class.

More information

Section Random Variables and Histograms

Section Random Variables and Histograms Section 3.1 - Random Variables and Histograms Definition: A random variable is a rule that assigns a number to each outcome of an experiment. Example 1: Suppose we toss a coin three times. Then we could

More information

Section Distributions of Random Variables

Section Distributions of Random Variables Section 8.1 - Distributions of Random Variables Definition: A random variable is a rule that assigns a number to each outcome of an experiment. Example 1: Suppose we toss a coin three times. Then we could

More information

5.2 Random Variables, Probability Histograms and Probability Distributions

5.2 Random Variables, Probability Histograms and Probability Distributions Chapter 5 5.2 Random Variables, Probability Histograms and Probability Distributions A random variable (r.v.) can be either continuous or discrete. It takes on the possible values of an experiment. It

More information

Chapter 8 Homework Solutions Compiled by Joe Kahlig. speed(x) freq 25 x < x < x < x < x < x < 55 5

Chapter 8 Homework Solutions Compiled by Joe Kahlig. speed(x) freq 25 x < x < x < x < x < x < 55 5 H homework problems, C-copyright Joe Kahlig Chapter Solutions, Page Chapter Homework Solutions Compiled by Joe Kahlig. (a) finite discrete (b) infinite discrete (c) continuous (d) finite discrete (e) continuous.

More information

Section 8.1 Distributions of Random Variables

Section 8.1 Distributions of Random Variables Section 8.1 Distributions of Random Variables Random Variable A random variable is a rule that assigns a number to each outcome of a chance experiment. There are three types of random variables: 1. Finite

More information

Section Distributions of Random Variables

Section Distributions of Random Variables Section 8.1 - Distributions of Random Variables Definition: A random variable is a rule that assigns a number to each outcome of an experiment. Example 1: Suppose we toss a coin three times. Then we could

More information

SECTION 4.4: Expected Value

SECTION 4.4: Expected Value 15 SECTION 4.4: Expected Value This section tells you why most all gambling is a bad idea. And also why carnival or amusement park games are a bad idea. Random Variables Definition: Random Variable A random

More information

Part 1 In which we meet the law of averages. The Law of Averages. The Expected Value & The Standard Error. Where Are We Going?

Part 1 In which we meet the law of averages. The Law of Averages. The Expected Value & The Standard Error. Where Are We Going? 1 The Law of Averages The Expected Value & The Standard Error Where Are We Going? Sums of random numbers The law of averages Box models for generating random numbers Sums of draws: the Expected Value Standard

More information

MATH 118 Class Notes For Chapter 5 By: Maan Omran

MATH 118 Class Notes For Chapter 5 By: Maan Omran MATH 118 Class Notes For Chapter 5 By: Maan Omran Section 5.1 Central Tendency Mode: the number or numbers that occur most often. Median: the number at the midpoint of a ranked data. Ex1: The test scores

More information

Chapter 5 Probability Distributions. Section 5-2 Random Variables. Random Variable Probability Distribution. Discrete and Continuous Random Variables

Chapter 5 Probability Distributions. Section 5-2 Random Variables. Random Variable Probability Distribution. Discrete and Continuous Random Variables Chapter 5 Probability Distributions Section 5-2 Random Variables 5-2 Random Variables 5-3 Binomial Probability Distributions 5-4 Mean, Variance and Standard Deviation for the Binomial Distribution Random

More information

Section 7.5 The Normal Distribution. Section 7.6 Application of the Normal Distribution

Section 7.5 The Normal Distribution. Section 7.6 Application of the Normal Distribution Section 7.6 Application of the Normal Distribution A random variable that may take on infinitely many values is called a continuous random variable. A continuous probability distribution is defined by

More information

MAKING SENSE OF DATA Essentials series

MAKING SENSE OF DATA Essentials series MAKING SENSE OF DATA Essentials series THE NORMAL DISTRIBUTION Copyright by City of Bradford MDC Prerequisites Descriptive statistics Charts and graphs The normal distribution Surveys and sampling Correlation

More information

FINAL REVIEW W/ANSWERS

FINAL REVIEW W/ANSWERS FINAL REVIEW W/ANSWERS ( 03/15/08 - Sharon Coates) Concepts to review before answering the questions: A population consists of the entire group of people or objects of interest to an investigator, while

More information

Chapter 8 Homework Solutions Compiled by Joe Kahlig

Chapter 8 Homework Solutions Compiled by Joe Kahlig homewk problems, B-copyright Joe Kahlig Chapter Solutions, Page Chapter omewk Solutions Compiled by Joe Kahlig 0. 0. 0. 0.. You are counting the number of games and there are a limited number of games

More information

STAT 3090 Test 2 - Version B Fall Student s Printed Name: PLEASE READ DIRECTIONS!!!!

STAT 3090 Test 2 - Version B Fall Student s Printed Name: PLEASE READ DIRECTIONS!!!! Student s Printed Name: Instructor: XID: Section #: Read each question very carefully. You are permitted to use a calculator on all portions of this exam. You are NOT allowed to use any textbook, notes,

More information

Contents. The Binomial Distribution. The Binomial Distribution The Normal Approximation to the Binomial Left hander example

Contents. The Binomial Distribution. The Binomial Distribution The Normal Approximation to the Binomial Left hander example Contents The Binomial Distribution The Normal Approximation to the Binomial Left hander example The Binomial Distribution When you flip a coin there are only two possible outcomes - heads or tails. This

More information

Consider the following examples: ex: let X = tossing a coin three times and counting the number of heads

Consider the following examples: ex: let X = tossing a coin three times and counting the number of heads Overview Both chapters and 6 deal with a similar concept probability distributions. The difference is that chapter concerns itself with discrete probability distribution while chapter 6 covers continuous

More information

STAT 201 Chapter 6. Distribution

STAT 201 Chapter 6. Distribution STAT 201 Chapter 6 Distribution 1 Random Variable We know variable Random Variable: a numerical measurement of the outcome of a random phenomena Capital letter refer to the random variable Lower case letters

More information

Section 8.4 The Binomial Distribution

Section 8.4 The Binomial Distribution Section 8.4 The Binomial Distribution Binomial Experiment A binomial experiment has the following properties: 1. The number of trials in the experiment is fixed. 2. There are two outcomes of each trial:

More information

Lecture 9. Probability Distributions

Lecture 9. Probability Distributions Lecture 9 Probability Distributions Outline 6-1 Introduction 6-2 Probability Distributions 6-3 Mean, Variance, and Expectation 6-4 The Binomial Distribution Outline 7-2 Properties of the Normal Distribution

More information

Math 1070 Sample Exam 2 Spring 2015

Math 1070 Sample Exam 2 Spring 2015 University of Connecticut Department of Mathematics Math 1070 Sample Exam 2 Spring 2015 Name: Instructor Name: Section: Exam 2 will cover Sections 4.6-4.7, 5.3-5.4, 6.1-6.4, and F.1-F.4. This sample exam

More information

Lesson 97 - Binomial Distributions IBHL2 - SANTOWSKI

Lesson 97 - Binomial Distributions IBHL2 - SANTOWSKI Lesson 97 - Binomial Distributions IBHL2 - SANTOWSKI Opening Exercise: Example #: (a) Use a tree diagram to answer the following: You throwing a bent coin 3 times where P(H) = / (b) THUS, find the probability

More information

Opening Exercise: Lesson 91 - Binomial Distributions IBHL2 - SANTOWSKI

Opening Exercise: Lesson 91 - Binomial Distributions IBHL2 - SANTOWSKI 08-0- Lesson 9 - Binomial Distributions IBHL - SANTOWSKI Opening Exercise: Example #: (a) Use a tree diagram to answer the following: You throwing a bent coin times where P(H) = / (b) THUS, find the probability

More information

Section 8.4 The Binomial Distribution. (a) Rolling a fair die 20 times and observing how many heads appear. s

Section 8.4 The Binomial Distribution. (a) Rolling a fair die 20 times and observing how many heads appear. s Section 8.4 The Binomial Distribution Binomial Experiment A binomial experiment has the following properties: 1. The number of trials in the experiment is fixed. 2. There are two outcomes of each trial:

More information

Bayes s Rule Example. defective. An MP3 player is selected at random and found to be defective. What is the probability it came from Factory I?

Bayes s Rule Example. defective. An MP3 player is selected at random and found to be defective. What is the probability it came from Factory I? Bayes s Rule Example A company manufactures MP3 players at two factories. Factory I produces 60% of the MP3 players and Factory II produces 40%. Two percent of the MP3 players produced at Factory I are

More information

ECON 214 Elements of Statistics for Economists 2016/2017

ECON 214 Elements of Statistics for Economists 2016/2017 ECON 214 Elements of Statistics for Economists 2016/2017 Topic The Normal Distribution Lecturer: Dr. Bernardin Senadza, Dept. of Economics bsenadza@ug.edu.gh College of Education School of Continuing and

More information

Statistical Methods in Practice STAT/MATH 3379

Statistical Methods in Practice STAT/MATH 3379 Statistical Methods in Practice STAT/MATH 3379 Dr. A. B. W. Manage Associate Professor of Mathematics & Statistics Department of Mathematics & Statistics Sam Houston State University Overview 6.1 Discrete

More information

TRUE-FALSE: Determine whether each of the following statements is true or false.

TRUE-FALSE: Determine whether each of the following statements is true or false. Chapter 6 Test Review Name TRUE-FALSE: Determine whether each of the following statements is true or false. 1) A random variable is continuous when the set of possible values includes an entire interval

More information

2011 Pearson Education, Inc

2011 Pearson Education, Inc Statistics for Business and Economics Chapter 4 Random Variables & Probability Distributions Content 1. Two Types of Random Variables 2. Probability Distributions for Discrete Random Variables 3. The Binomial

More information

5.4 Normal Approximation of the Binomial Distribution

5.4 Normal Approximation of the Binomial Distribution 5.4 Normal Approximation of the Binomial Distribution Bernoulli Trials have 3 properties: 1. Only two outcomes - PASS or FAIL 2. n identical trials Review from yesterday. 3. Trials are independent - probability

More information

A.REPRESENTATION OF DATA

A.REPRESENTATION OF DATA A.REPRESENTATION OF DATA (a) GRAPHS : PART I Q: Why do we need a graph paper? Ans: You need graph paper to draw: (i) Histogram (ii) Cumulative Frequency Curve (iii) Frequency Polygon (iv) Box-and-Whisker

More information

Lecture 9. Probability Distributions. Outline. Outline

Lecture 9. Probability Distributions. Outline. Outline Outline Lecture 9 Probability Distributions 6-1 Introduction 6- Probability Distributions 6-3 Mean, Variance, and Expectation 6-4 The Binomial Distribution Outline 7- Properties of the Normal Distribution

More information

Section 8.4 The Binomial Distribution

Section 8.4 The Binomial Distribution Section 84 The Binomial Distribution Binomial Experiment A binomial experiment has the following properties: 1 The number of trials in the experiment is fixed 2 There are two outcomes of each trial: success

More information

EXERCISES FOR PRACTICE SESSION 2 OF STAT CAMP

EXERCISES FOR PRACTICE SESSION 2 OF STAT CAMP EXERCISES FOR PRACTICE SESSION 2 OF STAT CAMP Note 1: The exercises below that are referenced by chapter number are taken or modified from the following open-source online textbook that was adapted by

More information

The Binomial Probability Distribution

The Binomial Probability Distribution The Binomial Probability Distribution MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2017 Objectives After this lesson we will be able to: determine whether a probability

More information

Example 1: Identify the following random variables as discrete or continuous: a) Weight of a package. b) Number of students in a first-grade classroom

Example 1: Identify the following random variables as discrete or continuous: a) Weight of a package. b) Number of students in a first-grade classroom Section 5-1 Probability Distributions I. Random Variables A variable x is a if the value that it assumes, corresponding to the of an experiment, is a or event. A random variable is if it potentially can

More information

AP Statistics Test 5

AP Statistics Test 5 AP Statistics Test 5 Name: Date: Period: ffl If X is a discrete random variable, the the mean of X and the variance of X are given by μ = E(X) = X xp (X = x); Var(X) = X (x μ) 2 P (X = x): ffl If X is

More information

Chapter 6: Random Variables. Ch. 6-3: Binomial and Geometric Random Variables

Chapter 6: Random Variables. Ch. 6-3: Binomial and Geometric Random Variables Chapter : Random Variables Ch. -3: Binomial and Geometric Random Variables X 0 2 3 4 5 7 8 9 0 0 P(X) 3???????? 4 4 When the same chance process is repeated several times, we are often interested in whether

More information

AP Statistics Section 6.1 Day 1 Multiple Choice Practice. a) a random variable. b) a parameter. c) biased. d) a random sample. e) a statistic.

AP Statistics Section 6.1 Day 1 Multiple Choice Practice. a) a random variable. b) a parameter. c) biased. d) a random sample. e) a statistic. A Statistics Section 6.1 Day 1 ultiple Choice ractice Name: 1. A variable whose value is a numerical outcome of a random phenomenon is called a) a random variable. b) a parameter. c) biased. d) a random

More information

Review. What is the probability of throwing two 6s in a row with a fair die? a) b) c) d) 0.333

Review. What is the probability of throwing two 6s in a row with a fair die? a) b) c) d) 0.333 Review In most card games cards are dealt without replacement. What is the probability of being dealt an ace and then a 3? Choose the closest answer. a) 0.0045 b) 0.0059 c) 0.0060 d) 0.1553 Review What

More information

Exam II Math 1342 Capters 3-5 HCCS. Name

Exam II Math 1342 Capters 3-5 HCCS. Name Exam II Math 1342 Capters 3-5 HCCS Name Date Provide an appropriate response. 1) A single six-sided die is rolled. Find the probability of rolling a number less than 3. A) 0.5 B) 0.1 C) 0.25 D 0.333 1)

More information

The normal distribution is a theoretical model derived mathematically and not empirically.

The normal distribution is a theoretical model derived mathematically and not empirically. Sociology 541 The Normal Distribution Probability and An Introduction to Inferential Statistics Normal Approximation The normal distribution is a theoretical model derived mathematically and not empirically.

More information

Chapter 4 and 5 Note Guide: Probability Distributions

Chapter 4 and 5 Note Guide: Probability Distributions Chapter 4 and 5 Note Guide: Probability Distributions Probability Distributions for a Discrete Random Variable A discrete probability distribution function has two characteristics: Each probability is

More information

(Practice Version) Midterm Exam 1

(Practice Version) Midterm Exam 1 EECS 126 Probability and Random Processes University of California, Berkeley: Fall 2014 Kannan Ramchandran September 19, 2014 (Practice Version) Midterm Exam 1 Last name First name SID Rules. DO NOT open

More information

Distribution of the Sample Mean

Distribution of the Sample Mean Distribution of the Sample Mean MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2018 Experiment (1 of 3) Suppose we have the following population : 4 8 1 2 3 4 9 1

More information

TOPIC: PROBABILITY DISTRIBUTIONS

TOPIC: PROBABILITY DISTRIBUTIONS TOPIC: PROBABILITY DISTRIBUTIONS There are two types of random variables: A Discrete random variable can take on only specified, distinct values. A Continuous random variable can take on any value within

More information

Chapter 4. Section 4.1 Objectives. Random Variables. Random Variables. Chapter 4: Probability Distributions

Chapter 4. Section 4.1 Objectives. Random Variables. Random Variables. Chapter 4: Probability Distributions Chapter 4: Probability s 4. Probability s 4. Binomial s Section 4. Objectives Distinguish between discrete random variables and continuous random variables Construct a discrete probability distribution

More information

The binomial distribution p314

The binomial distribution p314 The binomial distribution p314 Example: A biased coin (P(H) = p = 0.6) ) is tossed 5 times. Let X be the number of H s. Fine P(X = 2). This X is a binomial r. v. The binomial setting p314 1. There are

More information

Revision Pack 4. Probability Distributions. Doublestruck & CIE - Licensed to Brillantmont International School 1

Revision Pack 4. Probability Distributions. Doublestruck & CIE - Licensed to Brillantmont International School 1 S1 Revision Pack 4 Probability Distributions Doublestruck & CIE - Licensed to Brillantmont International School 1 1. Gohan throws a fair tetrahedral die with faces numbered 1, 2, 3, 4. If she throws an

More information

Probability Distributions

Probability Distributions Chapter 6 Discrete Probability Distributions Section 6-2 Probability Distributions Definitions Let S be the sample space of a probability experiment. A random variable X is a function from the set S into

More information

University of California, Los Angeles Department of Statistics. Normal distribution

University of California, Los Angeles Department of Statistics. Normal distribution University of California, Los Angeles Department of Statistics Statistics 110A Instructor: Nicolas Christou Normal distribution The normal distribution is the most important distribution. It describes

More information

Test 6A AP Statistics Name:

Test 6A AP Statistics Name: Test 6A AP Statistics Name: Part 1: Multiple Choice. Circle the letter corresponding to the best answer. 1. A marketing survey compiled data on the number of personal computers in households. If X = the

More information

Mathematical Concepts Joysheet 1 MAT 117, Spring 2011 D. Ivanšić. Name: Show all your work!

Mathematical Concepts Joysheet 1 MAT 117, Spring 2011 D. Ivanšić. Name: Show all your work! Mathematical Concepts Joysheet 1 Use your calculator to compute each expression to 6 significant digits accuracy. Write down thesequence of keys youentered inorder to compute each expression. Donot roundnumbers

More information

expl 1: Consider rolling two distinguishable, six-sided dice. Here is the sample space. Answer the questions that follow.

expl 1: Consider rolling two distinguishable, six-sided dice. Here is the sample space. Answer the questions that follow. General Education Statistics Class Notes Conditional Probability (Section 5.4) What is the probability you get a sum of 5 on two dice? Now assume one die is a 4. Does that affect the probability the sum

More information

Part 10: The Binomial Distribution

Part 10: The Binomial Distribution Part 10: The Binomial Distribution The binomial distribution is an important example of a probability distribution for a discrete random variable. It has wide ranging applications. One readily available

More information

Econ 6900: Statistical Problems. Instructor: Yogesh Uppal

Econ 6900: Statistical Problems. Instructor: Yogesh Uppal Econ 6900: Statistical Problems Instructor: Yogesh Uppal Email: yuppal@ysu.edu Lecture Slides 4 Random Variables Probability Distributions Discrete Distributions Discrete Uniform Probability Distribution

More information

d) Find the standard deviation of the random variable X.

d) Find the standard deviation of the random variable X. Q 1: The number of students using Math lab per day is found in the distribution below. x 6 8 10 12 14 P(x) 0.15 0.3 0.35 0.1 0.1 a) Find the mean for this probability distribution. b) Find the variance

More information

4.2 Bernoulli Trials and Binomial Distributions

4.2 Bernoulli Trials and Binomial Distributions Arkansas Tech University MATH 3513: Applied Statistics I Dr. Marcel B. Finan 4.2 Bernoulli Trials and Binomial Distributions A Bernoulli trial 1 is an experiment with exactly two outcomes: Success and

More information

Binomial Random Variables. Binomial Random Variables

Binomial Random Variables. Binomial Random Variables Bernoulli Trials Definition A Bernoulli trial is a random experiment in which there are only two possible outcomes - success and failure. 1 Tossing a coin and considering heads as success and tails as

More information

Math 1070 Final Exam Practice Spring 2014

Math 1070 Final Exam Practice Spring 2014 University of Connecticut Department of Mathematics Math 1070 Practice Spring 2014 Name: Instructor Name: Section: Read This First! This is a closed notes, closed book exam. You can not receive aid on

More information

Counting Basics. Venn diagrams

Counting Basics. Venn diagrams Counting Basics Sets Ways of specifying sets Union and intersection Universal set and complements Empty set and disjoint sets Venn diagrams Counting Inclusion-exclusion Multiplication principle Addition

More information

Have you ever wondered whether it would be worth it to buy a lottery ticket every week, or pondered on questions such as If I were offered a choice

Have you ever wondered whether it would be worth it to buy a lottery ticket every week, or pondered on questions such as If I were offered a choice Section 8.5: Expected Value and Variance Have you ever wondered whether it would be worth it to buy a lottery ticket every week, or pondered on questions such as If I were offered a choice between a million

More information

Normal distribution. We say that a random variable X follows the normal distribution if the probability density function of X is given by

Normal distribution. We say that a random variable X follows the normal distribution if the probability density function of X is given by Normal distribution The normal distribution is the most important distribution. It describes well the distribution of random variables that arise in practice, such as the heights or weights of people,

More information

MATH 112 Section 7.3: Understanding Chance

MATH 112 Section 7.3: Understanding Chance MATH 112 Section 7.3: Understanding Chance Prof. Jonathan Duncan Walla Walla University Autumn Quarter, 2007 Outline 1 Introduction to Probability 2 Theoretical vs. Experimental Probability 3 Advanced

More information

In a binomial experiment of n trials, where p = probability of success and q = probability of failure. mean variance standard deviation

In a binomial experiment of n trials, where p = probability of success and q = probability of failure. mean variance standard deviation Name In a binomial experiment of n trials, where p = probability of success and q = probability of failure mean variance standard deviation µ = n p σ = n p q σ = n p q Notation X ~ B(n, p) The probability

More information

The Normal Probability Distribution

The Normal Probability Distribution 1 The Normal Probability Distribution Key Definitions Probability Density Function: An equation used to compute probabilities for continuous random variables where the output value is greater than zero

More information

Applied Mathematics 12 Extra Practice Exercises Chapter 3

Applied Mathematics 12 Extra Practice Exercises Chapter 3 H E LP Applied Mathematics Extra Practice Exercises Chapter Tutorial., page 98. A bag contains 5 red balls, blue balls, and green balls. For each of the experiments described below, complete the given

More information

STAT 3090 Test 2 - Version B Fall Student s Printed Name: PLEASE READ DIRECTIONS!!!!

STAT 3090 Test 2 - Version B Fall Student s Printed Name: PLEASE READ DIRECTIONS!!!! STAT 3090 Test 2 - Fall 2015 Student s Printed Name: Instructor: XID: Section #: Read each question very carefully. You are permitted to use a calculator on all portions of this exam. You are NOT allowed

More information

6.1 Discrete & Continuous Random Variables. Nov 4 6:53 PM. Objectives

6.1 Discrete & Continuous Random Variables. Nov 4 6:53 PM. Objectives 6.1 Discrete & Continuous Random Variables examples vocab Objectives Today we will... - Compute probabilities using the probability distribution of a discrete random variable. - Calculate and interpret

More information

Probability Distributions. Definitions Discrete vs. Continuous Mean and Standard Deviation TI 83/84 Calculator Binomial Distribution

Probability Distributions. Definitions Discrete vs. Continuous Mean and Standard Deviation TI 83/84 Calculator Binomial Distribution Probability Distributions Definitions Discrete vs. Continuous Mean and Standard Deviation TI 83/84 Calculator Binomial Distribution Definitions Random Variable: a variable that has a single numerical value

More information

MATH1215: Mathematical Thinking Sec. 08 Spring Worksheet 9: Solution. x P(x)

MATH1215: Mathematical Thinking Sec. 08 Spring Worksheet 9: Solution. x P(x) N. Name: MATH: Mathematical Thinking Sec. 08 Spring 0 Worksheet 9: Solution Problem Compute the expected value of this probability distribution: x 3 8 0 3 P(x) 0. 0.0 0.3 0. Clearly, a value is missing

More information

the number of correct answers on question i. (Note that the only possible values of X i

the number of correct answers on question i. (Note that the only possible values of X i 6851_ch08_137_153 16/9/02 19:48 Page 137 8 8.1 (a) No: There is no fixed n (i.e., there is no definite upper limit on the number of defects). (b) Yes: It is reasonable to believe that all responses are

More information

Data Analytics (CS40003) Practice Set IV (Topic: Probability and Sampling Distribution)

Data Analytics (CS40003) Practice Set IV (Topic: Probability and Sampling Distribution) Data Analytics (CS40003) Practice Set IV (Topic: Probability and Sampling Distribution) I. Concept Questions 1. Give an example of a random variable in the context of Drawing a card from a deck of cards.

More information

Chapter 8. Variables. Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc.

Chapter 8. Variables. Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 8 Random Variables Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc. 8.1 What is a Random Variable? Random Variable: assigns a number to each outcome of a random circumstance, or,

More information

Simple Random Sample

Simple Random Sample Simple Random Sample A simple random sample (SRS) of size n consists of n elements from the population chosen in such a way that every set of n elements has an equal chance to be the sample actually selected.

More information

MATH 264 Problem Homework I

MATH 264 Problem Homework I MATH Problem Homework I Due to December 9, 00@:0 PROBLEMS & SOLUTIONS. A student answers a multiple-choice examination question that offers four possible answers. Suppose that the probability that the

More information

MANAGEMENT PRINCIPLES AND STATISTICS (252 BE)

MANAGEMENT PRINCIPLES AND STATISTICS (252 BE) MANAGEMENT PRINCIPLES AND STATISTICS (252 BE) Normal and Binomial Distribution Applied to Construction Management Sampling and Confidence Intervals Sr Tan Liat Choon Email: tanliatchoon@gmail.com Mobile:

More information

Binomial and Normal Distributions. Example: Determine whether the following experiments are binomial experiments. Explain.

Binomial and Normal Distributions. Example: Determine whether the following experiments are binomial experiments. Explain. Binomial and Normal Distributions Objective 1: Determining if an Experiment is a Binomial Experiment For an experiment to be considered a binomial experiment, four things must hold: 1. The experiment is

More information

Data that can be any numerical value are called continuous. These are usually things that are measured, such as height, length, time, speed, etc.

Data that can be any numerical value are called continuous. These are usually things that are measured, such as height, length, time, speed, etc. Chapter 8 Measures of Center Data that can be any numerical value are called continuous. These are usually things that are measured, such as height, length, time, speed, etc. Data that can only be integer

More information

Math 227 (Statistics) Chapter 6 Practice Test MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

Math 227 (Statistics) Chapter 6 Practice Test MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Math 227 (Statistics) Chapter 6 Practice Test MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Using the following uniform density curve, answer the

More information

Unit 04 Review. Probability Rules

Unit 04 Review. Probability Rules Unit 04 Review Probability Rules A sample space contains all the possible outcomes observed in a trial of an experiment, a survey, or some random phenomenon. The sum of the probabilities for all possible

More information

1. Steve says I have two children, one of which is a boy. Given this information, what is the probability that Steve has two boys?

1. Steve says I have two children, one of which is a boy. Given this information, what is the probability that Steve has two boys? Chapters 6 8 Review 1. Steve says I have two children, one of which is a boy. Given this information, what is the probability that Steve has two boys? (A) 1 (B) 3 1 (C) 3 (D) 4 1 (E) None of the above..

More information

Theoretical Foundations

Theoretical Foundations Theoretical Foundations Probabilities Monia Ranalli monia.ranalli@uniroma2.it Ranalli M. Theoretical Foundations - Probabilities 1 / 27 Objectives understand the probability basics quantify random phenomena

More information

Chapter 3 - Lecture 5 The Binomial Probability Distribution

Chapter 3 - Lecture 5 The Binomial Probability Distribution Chapter 3 - Lecture 5 The Binomial Probability October 12th, 2009 Experiment Examples Moments and moment generating function of a Binomial Random Variable Outline Experiment Examples A binomial experiment

More information

MATH 1300: Finite Mathematics EXAM 1 21 September 2017

MATH 1300: Finite Mathematics EXAM 1 21 September 2017 MATH 1300: Finite Mathematics EXAM 1 21 September 2017 NAME:...Grading Version B... Question Answer 1 $37,033.15 2 $10,338.10 3 $4409.12 4 $111.98 5 $2224.24 6 $302.50 7 $5626.65 8 x = 1, y = 1 9 No solution

More information

The Binomial Distribution

The Binomial Distribution The Binomial Distribution January 31, 2018 Contents The Binomial Distribution The Normal Approximation to the Binomial The Binomial Hypothesis Test Computing Binomial Probabilities in R 30 Problems The

More information

X = x p(x) 1 / 6 1 / 6 1 / 6 1 / 6 1 / 6 1 / 6. x = 1 x = 2 x = 3 x = 4 x = 5 x = 6 values for the random variable X

X = x p(x) 1 / 6 1 / 6 1 / 6 1 / 6 1 / 6 1 / 6. x = 1 x = 2 x = 3 x = 4 x = 5 x = 6 values for the random variable X Calculus II MAT 146 Integration Applications: Probability Calculating probabilities for discrete cases typically involves comparing the number of ways a chosen event can occur to the number of ways all

More information

Test - Sections 11-13

Test - Sections 11-13 Test - Sections 11-13 version 1 You have just been offered a job with medical benefits. In talking with the insurance salesperson you learn that the insurer uses the following probability calculations:

More information

Discrete Probability Distributions

Discrete Probability Distributions Discrete Probability Distributions Answers 1. Suppose a statistician working for CSULA Federal Credit Union collected data on ATM withdrawals for the population of the credit union s customers. The statistician

More information

The Binomial Distribution

The Binomial Distribution The Binomial Distribution January 31, 2019 Contents The Binomial Distribution The Normal Approximation to the Binomial The Binomial Hypothesis Test Computing Binomial Probabilities in R 30 Problems The

More information

Elementary Statistics Lecture 5

Elementary Statistics Lecture 5 Elementary Statistics Lecture 5 Sampling Distributions Chong Ma Department of Statistics University of South Carolina Chong Ma (Statistics, USC) STAT 201 Elementary Statistics 1 / 24 Outline 1 Introduction

More information

Math 166: Topics in Contemporary Mathematics II

Math 166: Topics in Contemporary Mathematics II Math 166: Topics in Contemporary Mathematics II Ruomeng Lan Texas A&M University October 15, 2014 Ruomeng Lan (TAMU) Math 166 October 15, 2014 1 / 12 Mean, Median and Mode Definition: 1. The average or

More information

What do you think "Binomial" involves?

What do you think Binomial involves? Learning Goals: * Define a binomial experiment (Bernoulli Trials). * Applying the binomial formula to solve problems. * Determine the expected value of a Binomial Distribution What do you think "Binomial"

More information

Statistics, Measures of Central Tendency I

Statistics, Measures of Central Tendency I Statistics, Measures of Central Tendency I We are considering a random variable X with a probability distribution which has some parameters. We want to get an idea what these parameters are. We perfom

More information

5.4 Normal Approximation of the Binomial Distribution Lesson MDM4U Jensen

5.4 Normal Approximation of the Binomial Distribution Lesson MDM4U Jensen 5.4 Normal Approximation of the Binomial Distribution Lesson MDM4U Jensen Review From Yesterday Bernoulli Trials have 3 properties: 1. 2. 3. Binomial Probability Distribution In a binomial experiment with

More information

Math 14 Lecture Notes Ch. 4.3

Math 14 Lecture Notes Ch. 4.3 4.3 The Binomial Distribution Example 1: The former Sacramento King's DeMarcus Cousins makes 77% of his free throws. If he shoots 3 times, what is the probability that he will make exactly 0, 1, 2, or

More information

STT315 Chapter 4 Random Variables & Probability Distributions AM KM

STT315 Chapter 4 Random Variables & Probability Distributions AM KM Before starting new chapter: brief Review from Algebra Combinations In how many ways can we select x objects out of n objects? In how many ways you can select 5 numbers out of 45 numbers ballot to win

More information