Chapter Six Probability Distributions

Size: px
Start display at page:

Download "Chapter Six Probability Distributions"

Transcription

1 6.1 Probability Distributions Discrete Random Variable Chapter Six Probability Distributions x P(x) Practice. Construct a probability distribution for the number of dogs each person has in the classroom. Mean or Expected Value Standard Deviation Binomial Distribution Four Characteristics 1.) 2.) 3.) 4.)

2 Practice. Determine if the following experiments represents a binomial experiment. If not, explain why. 1.) A random sample of 15 college seniors is obtained, and the individuals selected are asked to state their ages. 2.) An experimental drug is administered to 100 randomly selected individuals, with the number of individuals responding favorably recorded. 3.) A state lottery randomly selects 6 balls numbered 1 to 40. You choose six numbers and purchase a lottery ticket. The random variable represents the number of matches on your ticket to the numbers drawn in the lottery. 4.) From past records, a clothing store finds that 26% of people who enter the store will make a purchase. During a one-hour period, 18 people enter the store. The random variable represents the number of people who do not make a purchase. Formula P(x) ( n C x )(p x )(q n x ) n = p = q = x = Practice. Find the indicated probabilities. 5.) A surgical technique is performed on seven patients. You are told there is a 70% chance of success. Find the probability that the surgery is successful for a.) exactly five patients. b.) at least five patients. c.) less than five patients.

3 6.) Ten percent of adults say oatmeal raisin is their favorite cookie. You randomly select 12 adults and ask each to name his or her favorite cookie. Find the probability that the number who say oatmeal raisin is their favorite cookie is a.) exactly three. b.) at least three. c.) less than three. Mean Standard Deviation

4 The Normal Distribution (review) Chapter Seven The Normal Distribution The Standard Normal Distribution Mean = Standard Deviation = z-score - Area Under the Curve Area to the Left Practice. Find the following areas under the standard normal curve. 1.) To the left of z = ) To the left of z = ) To the left of z = -1.04

5 Area to the Right Practice. Find the following areas under the standard normal curve. 4.) To the right of z = ) To the right of z = ) To the right of z = Area Between Practice. Find the following areas under the standard normal curve. 7.) Between z = 0 and z = ) Between z = and z = ) Between z = and z = 0.04

6 Practice. Find the following probabilities. 10.) P(z 1.15) 11.) P(z 2.56) 12.) P( 2.71 z 1.5) 13.) P(z 3.88) 14.) P(z 4.71) The Normal Distribution (Again) Mean = Standard Deviation = x

7 Convert from a Normal Distribution to a Standard Normal Distribution z x Practice. Find the following probabilities. 1.) The weights of adult male beagles are normally distributed, with a mean of 25 pounds and a standard deviation of 3 pounds. A beagle is randomly selected. a.) Find the probability that the beagle s weight is less than 23 pounds. b.) Find the probability that the beagle s weight is between 23 and 25 pounds. c.) Find the probability that the beagle s weight is more than 27 pounds.

8 2.) The monthly utility bills in a city are normally distributed, with a mean of $100 and a standard deviation of $12. A utility bill is randomly selected. a.) Find the probability that the utility bill is less than $70. b.) Find the probability that the utility bill is between $90 and $120. c.) Find the probability that the utility bill is more than $ Backwards curve. Practice. Find the z-score(s) that corresponds to the given area under the 1.) The area to the left is

9 2.) The area to the right is ) The area to the right is ) The area to the left is ) P 42 6.) P 90 7.) P 5

10 Converting from a Standard Normal Distribution to a Normal Distribution x z σ μ 7.) The weights of the contents of a cereal box are normally distributed with a mean weight of 20 ounces and a standard deviation of 0.07 ounce. Boxes in the lower 5% do not meet the minimum weight requirements and must be repackaged. What is the minimum weight requirement for a cereal box? 8.) In a survey of men in the U.S. (ages 20-29), the mean height was 69.2 inches with a standard deviation of 2.9 inches. What height represents the 80 th percentile? 9.) On a dry surface, the braking distance (in meters) of a Pontiac Grand AM SE can be approximated by a normal distribution with a mean of 45.1 m and a standard deviation of 0.5 m. What is the shortest braking distance of a Pontiac Grand AM SE that can be in the top 15% of braking distances?

11 7.4 - The Central Limit Theorem - Example. Replacement times for TV sets are normally distributed with a mean of 8.2 years and a standard deviation of 2.1 years. a.) Find the probability that a randomly selected TV will have a replacement time less than 7 years. b.) If 28 TVs are randomly selected, find the probability that their sample mean is less than 7 years. The Central Limit Theorem Used when finding the probability of the mean of a sample. x μ x z where μ μ and σ x x σ x σ n or x μ z σ n

12 Practice. Find the following probabilities. 1.) Cans of Coca-Cola are filled so that the actual amount have a mean of 12.0 oz and a standard deviation of 0.31 oz. Find the probability that sample of 36 cans will have a mean amount of at least oz. 2.) Standardized scores are normally distributed with a mean of 550 and a standard deviation of 110. If 25 test scores are randomly chosen, find the probability the mean score is between 385 and ) The reading speed of second grade students is approximately normal, with a mean of 90 words per minute (wpm) and a standard deviation of 10 wpm. a.) What is the probability a randomly selected student will read more than 95 words per minute?

13 b.) What is the probability that a random sample of 14 second grade students results in a mean reading rate of less than 95 words per minute? c.) What is the probability that a random sample of 34 second grade students results in a mean reading rate more than 95 words per minute?

No, because np = 100(0.02) = 2. The value of np must be greater than or equal to 5 to use the normal approximation.

No, because np = 100(0.02) = 2. The value of np must be greater than or equal to 5 to use the normal approximation. 1) If n 100 and p 0.02 in a binomial experiment, does this satisfy the rule for a normal approximation? Why or why not? No, because np 100(0.02) 2. The value of np must be greater than or equal to 5 to

More information

NORMAL RANDOM VARIABLES (Normal or gaussian distribution)

NORMAL RANDOM VARIABLES (Normal or gaussian distribution) NORMAL RANDOM VARIABLES (Normal or gaussian distribution) Many variables, as pregnancy lengths, foot sizes etc.. exhibit a normal distribution. The shape of the distribution is a symmetric bell shape.

More information

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 - Would the correlation between x and y in the table above be positive or negative? The correlation is negative. -

More information

Density curves. (James Madison University) February 4, / 20

Density curves. (James Madison University) February 4, / 20 Density curves Figure 6.2 p 230. A density curve is always on or above the horizontal axis, and has area exactly 1 underneath it. A density curve describes the overall pattern of a distribution. Example

More information

Example - Let X be the number of boys in a 4 child family. Find the probability distribution table:

Example - Let X be the number of boys in a 4 child family. Find the probability distribution table: Chapter8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables tthe value of the result of the probability experiment is a RANDOM VARIABLE. Example - Let X be the number

More information

Example. Chapter 8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables

Example. Chapter 8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables Chapter 8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables You are dealt a hand of 5 cards. Find the probability distribution table for the number of hearts. Graph

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

Chapter Seven. The Normal Distribution

Chapter Seven. The Normal Distribution Chapter Seven The Normal Distribution 7-1 Introduction Many continuous variables have distributions that are bellshaped and are called approximately normally distributed variables, such as the heights

More information

Study Guide: Chapter 5, Sections 1 thru 3 (Probability Distributions)

Study Guide: Chapter 5, Sections 1 thru 3 (Probability Distributions) Study Guide: Chapter 5, Sections 1 thru 3 (Probability Distributions) Name SHORT ANSWER. 1) Fill in the missing value so that the following table represents a probability distribution. x 1 2 3 4 P(x) 0.09

More information

Chapter 6. The Normal Probability Distributions

Chapter 6. The Normal Probability Distributions Chapter 6 The Normal Probability Distributions 1 Chapter 6 Overview Introduction 6-1 Normal Probability Distributions 6-2 The Standard Normal Distribution 6-3 Applications of the Normal Distribution 6-5

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

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

Chapter 4 and Chapter 5 Test Review Worksheet

Chapter 4 and Chapter 5 Test Review Worksheet Name: Date: Hour: Chapter 4 and Chapter 5 Test Review Worksheet You must shade all provided graphs, you must round all z-scores to 2 places after the decimal, you must round all probabilities to at least

More information

What is the probability of success? Failure? How could we do this simulation using a random number table?

What is the probability of success? Failure? How could we do this simulation using a random number table? Probability Ch.4, sections 4.2 & 4.3 Binomial and Geometric Distributions Name: Date: Pd: 4.2. What is a binomial distribution? How do we find the probability of success? Suppose you have three daughters.

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

Lecture 6: Chapter 6

Lecture 6: Chapter 6 Lecture 6: Chapter 6 C C Moxley UAB Mathematics 3 October 16 6.1 Continuous Probability Distributions Last week, we discussed the binomial probability distribution, which was discrete. 6.1 Continuous Probability

More information

AMS7: WEEK 4. CLASS 3

AMS7: WEEK 4. CLASS 3 AMS7: WEEK 4. CLASS 3 Sampling distributions and estimators. Central Limit Theorem Normal Approximation to the Binomial Distribution Friday April 24th, 2015 Sampling distributions and estimators REMEMBER:

More information

ECON 214 Elements of Statistics for Economists

ECON 214 Elements of Statistics for Economists ECON 214 Elements of Statistics for Economists Session 7 The Normal Distribution Part 1 Lecturer: Dr. Bernardin Senadza, Dept. of Economics Contact Information: bsenadza@ug.edu.gh College of Education

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

Section 6.5. The Central Limit Theorem

Section 6.5. The Central Limit Theorem Section 6.5 The Central Limit Theorem Idea Will allow us to combine the theory from 6.4 (sampling distribution idea) with our central limit theorem and that will allow us the do hypothesis testing in the

More information

Binomial Distributions

Binomial Distributions Binomial Distributions Binomial Experiment The experiment is repeated for a fixed number of trials, where each trial is independent of the other trials There are only two possible outcomes of interest

More information

Example - Let X be the number of boys in a 4 child family. Find the probability distribution table:

Example - Let X be the number of boys in a 4 child family. Find the probability distribution table: Chapter7 Probability Distributions and Statistics Distributions of Random Variables tthe value of the result of the probability experiment is a RANDOM VARIABLE. Example - Let X be the number of boys in

More information

Chapter 7: Sampling Distributions Chapter 7: Sampling Distributions

Chapter 7: Sampling Distributions Chapter 7: Sampling Distributions Chapter 7: Sampling Distributions Objectives: Students will: Define a sampling distribution. Contrast bias and variability. Describe the sampling distribution of a proportion (shape, center, and spread).

More information

AP * Statistics Review

AP * Statistics Review AP * Statistics Review Normal Models and Sampling Distributions Teacher Packet AP* is a trademark of the College Entrance Examination Board. The College Entrance Examination Board was not involved in the

More information

Math 14, Homework 6.2 p. 337 # 3, 4, 9, 10, 15, 18, 19, 21, 22 Name

Math 14, Homework 6.2 p. 337 # 3, 4, 9, 10, 15, 18, 19, 21, 22 Name Name 3. Population in U.S. Jails The average daily jail population in the United States is 706,242. If the distribution is normal and the standard deviation is 52,145, find the probability that on a randomly

More information

Section Introduction to Normal Distributions

Section Introduction to Normal Distributions Section 6.1-6.2 Introduction to Normal Distributions 2012 Pearson Education, Inc. All rights reserved. 1 of 105 Section 6.1-6.2 Objectives Interpret graphs of normal probability distributions Find areas

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

Homework: Due Wed, Nov 3 rd Chapter 8, # 48a, 55c and 56 (count as 1), 67a

Homework: Due Wed, Nov 3 rd Chapter 8, # 48a, 55c and 56 (count as 1), 67a Homework: Due Wed, Nov 3 rd Chapter 8, # 48a, 55c and 56 (count as 1), 67a Announcements: There are some office hour changes for Nov 5, 8, 9 on website Week 5 quiz begins after class today and ends at

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

LECTURE 6 DISTRIBUTIONS

LECTURE 6 DISTRIBUTIONS LECTURE 6 DISTRIBUTIONS OVERVIEW Uniform Distribution Normal Distribution Random Variables Continuous Distributions MOST OF THE SLIDES ADOPTED FROM OPENINTRO STATS BOOK. NORMAL DISTRIBUTION Unimodal and

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

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

Using the Central Limit Theorem It is important for you to understand when to use the CLT. If you are being asked to find the probability of the

Using the Central Limit Theorem It is important for you to understand when to use the CLT. If you are being asked to find the probability of the Using the Central Limit Theorem It is important for you to understand when to use the CLT. If you are being asked to find the probability of the mean, use the CLT for the mean. If you are being asked to

More information

Chapter 6 Continuous Probability Distributions. Learning objectives

Chapter 6 Continuous Probability Distributions. Learning objectives Chapter 6 Continuous s Slide 1 Learning objectives 1. Understand continuous probability distributions 2. Understand Uniform distribution 3. Understand Normal distribution 3.1. Understand Standard normal

More information

CH 5 Normal Probability Distributions Properties of the Normal Distribution

CH 5 Normal Probability Distributions Properties of the Normal Distribution Properties of the Normal Distribution Example A friend that is always late. Let X represent the amount of minutes that pass from the moment you are suppose to meet your friend until the moment your friend

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

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

Activity #17b: Central Limit Theorem #2. 1) Explain the Central Limit Theorem in your own words.

Activity #17b: Central Limit Theorem #2. 1) Explain the Central Limit Theorem in your own words. Activity #17b: Central Limit Theorem #2 1) Explain the Central Limit Theorem in your own words. Importance of the CLT: You can standardize and use normal distribution tables to calculate probabilities

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

2.) What is the set of outcomes that describes the event that at least one of the items selected is defective? {AD, DA, DD}

2.) What is the set of outcomes that describes the event that at least one of the items selected is defective? {AD, DA, DD} Math 361 Practice Exam 2 (Use this information for questions 1 3) At the end of a production run manufacturing rubber gaskets, items are sampled at random and inspected to determine if the item is Acceptable

More information

Math 251: Practice Questions Hints and Answers. Review II. Questions from Chapters 4 6

Math 251: Practice Questions Hints and Answers. Review II. Questions from Chapters 4 6 Math 251: Practice Questions Hints and Answers Review II. Questions from Chapters 4 6 II.A Probability II.A.1. The following is from a sample of 500 bikers who attended the annual rally in Sturgis South

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Exam Name The bar graph shows the number of tickets sold each week by the garden club for their annual flower show. ) During which week was the most number of tickets sold? ) A) Week B) Week C) Week 5

More information

Exercise Set 1 The normal distribution and sampling distributions

Exercise Set 1 The normal distribution and sampling distributions Eercise Set 1 The normal distribution and sampling distributions 1). An orange juice producer buys all his oranges from a large orange grove. The amount of juice squeezed from each of these oranges is

More information

AMS 7 Sampling Distributions, Central limit theorem, Confidence Intervals Lecture 4

AMS 7 Sampling Distributions, Central limit theorem, Confidence Intervals Lecture 4 AMS 7 Sampling Distributions, Central limit theorem, Confidence Intervals Lecture 4 Department of Applied Mathematics and Statistics, University of California, Santa Cruz Summer 2014 1 / 26 Sampling Distributions!!!!!!

More information

The Binomial Distribution

The Binomial Distribution The Binomial Distribution Properties of a Binomial Experiment 1. It consists of a fixed number of observations called trials. 2. Each trial can result in one of only two mutually exclusive outcomes labeled

More information

7 THE CENTRAL LIMIT THEOREM

7 THE CENTRAL LIMIT THEOREM CHAPTER 7 THE CENTRAL LIMIT THEOREM 373 7 THE CENTRAL LIMIT THEOREM Figure 7.1 If you want to figure out the distribution of the change people carry in their pockets, using the central limit theorem and

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

The Normal Approximation to the Binomial

The Normal Approximation to the Binomial Lecture 16 The Normal Approximation to the Binomial We can calculate l binomial i probabilities bbilii using The binomial formula The cumulative binomial tables When n is large, and p is not too close

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Ch. 8 Sampling Distributions 8.1 Distribution of the Sample Mean 1 Describe the distribution of the sample mean: normal population. MULTIPLE CHOICE. Choose the one alternative that best completes the statement

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

MA131 Lecture 8.2. The normal distribution curve can be considered as a probability distribution curve for normally distributed variables.

MA131 Lecture 8.2. The normal distribution curve can be considered as a probability distribution curve for normally distributed variables. Normal distribution curve as probability distribution curve The normal distribution curve can be considered as a probability distribution curve for normally distributed variables. The area under the normal

More information

Chapter 6: Random Variables

Chapter 6: Random Variables Chapter 6: Random Variables Section 6. The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Chapter 6 Random Variables 6.1 Discrete and Continuous Random Variables 6. 6.3 Binomial and

More information

Name PID Section # (enrolled)

Name PID Section # (enrolled) STT 315 - Lecture 3 Instructor: Aylin ALIN 04/02/2014 Midterm # 2 A Name PID Section # (enrolled) * The exam is closed book and 80 minutes. * You may use a calculator and the formula sheet that you brought

More information

Midterm Exam III Review

Midterm Exam III Review Midterm Exam III Review Dr. Joseph Brennan Math 148, BU Dr. Joseph Brennan (Math 148, BU) Midterm Exam III Review 1 / 25 Permutations and Combinations ORDER In order to count the number of possible ways

More information

Review of commonly missed questions on the online quiz. Lecture 7: Random variables] Expected value and standard deviation. Let s bet...

Review of commonly missed questions on the online quiz. Lecture 7: Random variables] Expected value and standard deviation. Let s bet... Recap Review of commonly missed questions on the online quiz Lecture 7: ] Statistics 101 Mine Çetinkaya-Rundel OpenIntro quiz 2: questions 4 and 5 September 20, 2011 Statistics 101 (Mine Çetinkaya-Rundel)

More information

MidTerm 1) Find the following (round off to one decimal place):

MidTerm 1) Find the following (round off to one decimal place): MidTerm 1) 68 49 21 55 57 61 70 42 59 50 66 99 Find the following (round off to one decimal place): Mean = 58:083, round off to 58.1 Median = 58 Range = max min = 99 21 = 78 St. Deviation = s = 8:535,

More information

MATH 104 CHAPTER 5 page 1 NORMAL DISTRIBUTION

MATH 104 CHAPTER 5 page 1 NORMAL DISTRIBUTION MATH 104 CHAPTER 5 page 1 NORMAL DISTRIBUTION We have examined discrete random variables, those random variables for which we can list the possible values. We will now look at continuous random variables.

More information

The graph of a normal curve is symmetric with respect to the line x = µ, and has points of

The graph of a normal curve is symmetric with respect to the line x = µ, and has points of Stat 400, section 4.3 Normal Random Variables notes prepared by Tim Pilachowski Another often-useful probability density function is the normal density function, which graphs as the familiar bell-shaped

More information

. 13. The maximum error (margin of error) of the estimate for μ (based on known σ) is:

. 13. The maximum error (margin of error) of the estimate for μ (based on known σ) is: Statistics Sample Exam 3 Solution Chapters 6 & 7: Normal Probability Distributions & Estimates 1. What percent of normally distributed data value lie within 2 standard deviations to either side of the

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

Chapter. Section 4.2. Chapter 4. Larson/Farber 5 th ed 1. Chapter Outline. Discrete Probability Distributions. Section 4.

Chapter. Section 4.2. Chapter 4. Larson/Farber 5 th ed 1. Chapter Outline. Discrete Probability Distributions. Section 4. Chapter Discrete Probability s Chapter Outline 1 Probability s 2 Binomial s 3 More Discrete Probability s Copyright 2015, 2012, and 2009 Pearson Education, Inc 1 Copyright 2015, 2012, and 2009 Pearson

More information

Honors Statistics. Daily Agenda

Honors Statistics. Daily Agenda Honors Statistics Aug 23-8:26 PM Daily Agenda 1. Review OTL C6#4 Chapter 6.2 rules for means and variances Aug 23-8:31 PM 1 Nov 21-8:16 PM Working out Choose a person aged 19 to 25 years at random 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

Math Tech IIII, May 7

Math Tech IIII, May 7 Math Tech IIII, May 7 The Normal Probability Models Book Sections: 5.1, 5.2, & 5.3 Essential Questions: How can I use the normal distribution to compute probability? Standards: S.ID.4 Properties of the

More information

1. The data in the following table represent the number of miles per gallon achieved on the highway for compact cars for the model year 2005.

1. The data in the following table represent the number of miles per gallon achieved on the highway for compact cars for the model year 2005. Millersville University Name Answer Key Department of Mathematics MATH 130, Elements of Statistics I, Test 2 March 5, 2010, 10:00AM-10:50AM Please answer the following questions. Your answers will be evaluated

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

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 Central Limit Theorem for Sample Means (Averages)

The Central Limit Theorem for Sample Means (Averages) The Central Limit Theorem for Sample Means (Averages) By: OpenStaxCollege Suppose X is a random variable with a distribution that may be known or unknown (it can be any distribution). Using a subscript

More information

Lecture 7 Random Variables

Lecture 7 Random Variables Lecture 7 Random Variables Definition: A random variable is a variable whose value is a numerical outcome of a random phenomenon, so its values are determined by chance. We shall use letters such as X

More information

Chapter 6 Section Review day s.notebook. May 11, Honors Statistics. Aug 23-8:26 PM. 3. Review team test.

Chapter 6 Section Review day s.notebook. May 11, Honors Statistics. Aug 23-8:26 PM. 3. Review team test. Honors Statistics Aug 23-8:26 PM 3. Review team test Aug 23-8:31 PM 1 Nov 27-10:28 PM 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 6.10 6.11 6.12 Nov 27-9:53 PM 2 May 8-7:44 PM May 1-9:09 PM 3 Dec 1-2:08 PM Sep

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

CHAPTER 5 SAMPLING DISTRIBUTIONS

CHAPTER 5 SAMPLING DISTRIBUTIONS CHAPTER 5 SAMPLING DISTRIBUTIONS Sampling Variability. We will visualize our data as a random sample from the population with unknown parameter μ. Our sample mean Ȳ is intended to estimate population mean

More information

Lecture 12. Some Useful Continuous Distributions. The most important continuous probability distribution in entire field of statistics.

Lecture 12. Some Useful Continuous Distributions. The most important continuous probability distribution in entire field of statistics. ENM 207 Lecture 12 Some Useful Continuous Distributions Normal Distribution The most important continuous probability distribution in entire field of statistics. Its graph, called the normal curve, is

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

Stat 210 Exam Two. MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

Stat 210 Exam Two. MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Stat 210 Exam Two Read these directions carefully. Take your time and check your work. Many students do not take enough time on their tests. Each problem is worth four points. You may choose exactly question

More information

Note: Some questions require the use of either a standard normal probability table or technology that can calculate normal probabilities.

Note: Some questions require the use of either a standard normal probability table or technology that can calculate normal probabilities. Chapter 6 Review (6.1-6.2) Chapter 6 Test B Multiple Choice Note: Some questions require the use of either a standard normal probability table or technology that can calculate normal probabilities. Section

More information

Chapter 5 Discrete Probability Distributions. Random Variables Discrete Probability Distributions Expected Value and Variance

Chapter 5 Discrete Probability Distributions. Random Variables Discrete Probability Distributions Expected Value and Variance Chapter 5 Discrete Probability Distributions Random Variables Discrete Probability Distributions Expected Value and Variance.40.30.20.10 0 1 2 3 4 Random Variables A random variable is a numerical description

More information

Part V - Chance Variability

Part V - Chance Variability Part V - Chance Variability Dr. Joseph Brennan Math 148, BU Dr. Joseph Brennan (Math 148, BU) Part V - Chance Variability 1 / 78 Law of Averages In Chapter 13 we discussed the Kerrich coin-tossing experiment.

More information

Honors Statistics. Daily Agenda

Honors Statistics. Daily Agenda Honors Statistics Daily Agenda 1. Review OTL C6#5 2. Quiz Section 6.1 A-Skip 35, 39, 40 Crickets The length in inches of a cricket chosen at random from a field is a random variable X with mean 1.2 inches

More information

PRINTABLE VERSION. Quiz 6. Suppose that x is normally distributed with a mean of 20 and a standard deviation of 3. What is P(16.91 x 24.59)?

PRINTABLE VERSION. Quiz 6. Suppose that x is normally distributed with a mean of 20 and a standard deviation of 3. What is P(16.91 x 24.59)? PRINTABLE VERSION Quiz 6 Question 1 Suppose that x is normally distributed with a mean of 20 and a standard deviation of 3. What is P(16.91 x 24.59)? a) 0.348 b) 0.438 c) 0.353 d) 0.437 e) 0.785 Question

More information

Introduction to Business Statistics QM 120 Chapter 6

Introduction to Business Statistics QM 120 Chapter 6 DEPARTMENT OF QUANTITATIVE METHODS & INFORMATION SYSTEMS Introduction to Business Statistics QM 120 Chapter 6 Spring 2008 Chapter 6: Continuous Probability Distribution 2 When a RV x is discrete, we can

More information

Math 227 Practice Test 2 Sec Name

Math 227 Practice Test 2 Sec Name Math 227 Practice Test 2 Sec 4.4-6.2 Name Find the indicated probability. ) A bin contains 64 light bulbs of which 0 are defective. If 5 light bulbs are randomly selected from the bin with replacement,

More information

STT 315 Practice Problems Chapter 3.7 and 4

STT 315 Practice Problems Chapter 3.7 and 4 STT 315 Practice Problems Chapter 3.7 and 4 Answer the question True or False. 1) The number of children in a family can be modelled using a continuous random variable. 2) For any continuous probability

More information

Introduction to Statistics I

Introduction to Statistics I Introduction to Statistics I Keio University, Faculty of Economics Continuous random variables Simon Clinet (Keio University) Intro to Stats November 1, 2018 1 / 18 Definition (Continuous random variable)

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

Uniform Probability Distribution. Continuous Random Variables &

Uniform Probability Distribution. Continuous Random Variables & Continuous Random Variables & What is a Random Variable? It is a quantity whose values are real numbers and are determined by the number of desired outcomes of an experiment. Is there any special Random

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

Problem Set 07 Discrete Random Variables

Problem Set 07 Discrete Random Variables Name Problem Set 07 Discrete Random Variables MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the mean of the random variable. 1) The random

More information

1. (9; 3ea) The table lists the survey results of 100 non-senior students. Math major Art major Biology major

1. (9; 3ea) The table lists the survey results of 100 non-senior students. Math major Art major Biology major Math 54 Test #2(Chapter 4, 5, 6, 7) Name: Show all necessary work for full credit. You may use graphing calculators for your calculation, but you must show all detail and use the proper notations. Total

More information

Previously, when making inferences about the population mean, μ, we were assuming the following simple conditions:

Previously, when making inferences about the population mean, μ, we were assuming the following simple conditions: Chapter 17 Inference about a Population Mean Conditions for inference Previously, when making inferences about the population mean, μ, we were assuming the following simple conditions: (1) Our data (observations)

More information

Statistics 511 Supplemental Materials

Statistics 511 Supplemental Materials Gaussian (or Normal) Random Variable In this section we introduce the Gaussian Random Variable, which is more commonly referred to as the Normal Random Variable. This is a random variable that has a bellshaped

More information

A continuous random variable is one that can theoretically take on any value on some line interval. We use f ( x)

A continuous random variable is one that can theoretically take on any value on some line interval. We use f ( x) Section 6-2 I. Continuous Probability Distributions A continuous random variable is one that can theoretically take on any value on some line interval. We use f ( x) to represent a probability density

More information

(j) Find the first quartile for a standard normal distribution.

(j) Find the first quartile for a standard normal distribution. Examples for Chapter 5 Normal Probability Distributions Math 1040 1 Section 5.1 1. Heights of males at a certain university are approximately normal with a mean of 70.9 inches and a standard deviation

More information

Lecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series. Slide 1

Lecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series. Slide 1 Lecture Slides Elementary Statistics Tenth Edition and the Triola Statistics Series by Mario F. Triola Slide 1 Chapter 6 Normal Probability Distributions 6-1 Overview 6-2 The Standard Normal Distribution

More information

Shifting our focus. We were studying statistics (data, displays, sampling...) The next few lectures focus on probability (randomness) Why?

Shifting our focus. We were studying statistics (data, displays, sampling...) The next few lectures focus on probability (randomness) Why? Probability Introduction Shifting our focus We were studying statistics (data, displays, sampling...) The next few lectures focus on probability (randomness) Why? What is Probability? Probability is used

More information

Chapter 9. Sampling Distributions. A sampling distribution is created by, as the name suggests, sampling.

Chapter 9. Sampling Distributions. A sampling distribution is created by, as the name suggests, sampling. Chapter 9 Sampling Distributions 9.1 Sampling Distributions A sampling distribution is created by, as the name suggests, sampling. The method we will employ on the rules of probability and the laws of

More information

8.2 The Standard Deviation as a Ruler Chapter 8 The Normal and Other Continuous Distributions 8-1

8.2 The Standard Deviation as a Ruler Chapter 8 The Normal and Other Continuous Distributions 8-1 8.2 The Standard Deviation as a Ruler Chapter 8 The Normal and Other Continuous Distributions For Example: On August 8, 2011, the Dow dropped 634.8 points, sending shock waves through the financial community.

More information

Chapter 7. Sampling Distributions

Chapter 7. Sampling Distributions Chapter 7 Sampling Distributions Section 7.1 Sampling Distributions and the Central Limit Theorem Sampling Distributions Sampling distribution The probability distribution of a sample statistic. Formed

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

NORMAL PROBABILITY DISTRIBUTIONS

NORMAL PROBABILITY DISTRIBUTIONS 5 CHAPTER NORMAL PROBABILITY DISTRIBUTIONS 5.1 Introduction to Normal Distributions and the Standard Normal Distribution 5.2 Normal Distributions: Finding Probabilities 5.3 Normal Distributions: Finding

More information