Mr. Orchard s Math 141 WIR 8.5, 8.6, 5.1 Week 13

Size: px
Start display at page:

Download "Mr. Orchard s Math 141 WIR 8.5, 8.6, 5.1 Week 13"

Transcription

1 1. Find the following probabilities, where Z is a random variable with a standard normal distribution and X is a normal random variable with mean µ = 380 and standard deviation σ = 21: (Round your answers to four decimal places.) (a) P ( 1 Z 1) (b) P (X < 419) (c) P (390 X < 414) (d) P (Z 0.61) (e) P (X = 380)

2 2. Let Z be the standard normal random variable. Find the values of a that satisfy the given probabilities: (Round your answer to four decimal places.) (a) P (Z < a) = (b) P (Z a) = (c) P ( a < Z < a) = Let X be a normal random variable with a mean of 80 and a standard deviation of 4. Find the values of A and B such that P (A X < B) = if A and B are symmetric about the mean. (Round to four decimal places.)

3 4. The number of chocolate chips in certain brand s bags are normally distributed with a mean of 291 chips and a standard deviation of 18 chips. (a) What is the minimum number of chocolate chips needed in bag to have a bag in the top 1% of number of chocolate chips? (Round to the nearest chocolate chip.) (b) What is the probability that a bag has more than 300 chocolate chips? (Round to four decimal places.) (c) What is the probability that a bag has more than 250, but less than or equal to 490 chocolate chips? (Round to four decimal places.) 5. A company manufactures electric light bulbs. Labratory tests show that the lives of the bulbs are normally distributed with a mean of 800 hours and a variance of hours 2. What is the probability that one of these light bulbs selected at random will burn for the following times? (Round to four decimal places.) (a) between 800 and 950 hours (b) more than 950 hours (c) between 650 and 850 hours

4 6. One way to curve a test is to give the top 15% of the class an A, the next 25% a B, the next 30% a C, the next 20% a D, and the bottom 10% an F. If the grades are normally distributed with a mean of 64 and a standard deviation of 15, find the point cut off for each letter grade. (Round your answers to two decimal places.) 7. Find the accumulated amount at the end of 15 months on a $1800 bank deposit paying simple interest at a rate of 7% per year. Round your answer to the nearest cent. 8. Determine the simple interest rate at which $1200 will grow to $1252 in 8 months. Round your answer to one decimal place. 9. Four and a half years ago, Chris invested $10,000 in a retirement fund that grew at a rate of 11.14% per year compounded quarterly. What is her account worth now? Round your answer to the nearest cent.

5 10. A young man is the beneficiary of a trust fund established for him 25 years ago. If the original amount placed in the trust was $40,000, and it grew at 10% per year, how much money has the account earned in interest if the account is compounded (round your answers to the nearest cent) (a) annually? (b) quarterly? (c) monthly? (d) continuously? 11. Bank A offers a bank account compounded quarterly at a nominal rate of 4.9% per year. Bank B offers an account compounded continuously at a rate of 4.8% per year. Determine which account is better for your money by comparing effective rates of interest.

6 12. Bank A offers a loan compounded twice a year at a nominal rate of 10.5% per year. Bank B offers a loan at a yearly rate of 10.3% compounded monthly. Determine which loan is the better offer by comparing effective rates of interest. 13. A bank account with an interest rate of 10% per year compounded continuously currently has $15,000 in it. (a) How much was put into the account when it was opened 10 years ago? Round your asnwer to the nearest cent. (b) What is the effective rate of interest of this account? Round your answer to two decimal places.

Section 5.1 Compound Interest

Section 5.1 Compound Interest Section 5.1 Compound Interest Simple Interest Formulas: Interest: Accumulated amount: I = Prt A = P (1 + rt) Here P is the principal (money you start out with), r is the interest rate (as a decimal), and

More information

Section 3.4 The Normal Distribution

Section 3.4 The Normal Distribution Section 3.4 The Normal Distribution Properties of the Normal Distribution Curve 1. We denote the normal random variable with X = x. 2. The curve has a peak at x = µ. 3. The curve is symmetric about the

More information

Section 5.1 Compound Interest

Section 5.1 Compound Interest Section 5.1 Compound Interest Simple Interest Formulas: Interest: Accumulated amount: I = P rt A = P (1 + rt) Here P is the principal (money you start out with), r is the interest rate (as a decimal),

More information

SECTION 6.1: Simple and Compound Interest

SECTION 6.1: Simple and Compound Interest 1 SECTION 6.1: Simple and Compound Interest Chapter 6 focuses on and various financial applications of interest. GOAL: Understand and apply different types of interest. Simple Interest If a sum of money

More information

Section 8.3 Compound Interest

Section 8.3 Compound Interest Section 8.3 Compound Interest Objectives 1. Use the compound interest formulas. 2. Calculate present value. 3. Understand and compute effective annual yield. 4/24/2013 Section 8.3 1 Compound interest is

More information

A LEVEL MATHEMATICS QUESTIONBANKS NORMAL DISTRIBUTION - BASIC

A LEVEL MATHEMATICS QUESTIONBANKS NORMAL DISTRIBUTION - BASIC 1. The random variable X has a normal distribution with mean 5 and standard deviation 2. Find: a) P(X

More information

Chapter Seven: Confidence Intervals and Sample Size

Chapter Seven: Confidence Intervals and Sample Size Chapter Seven: Confidence Intervals and Sample Size A point estimate is: The best point estimate of the population mean µ is the sample mean X. Three Properties of a Good Estimator 1. Unbiased 2. Consistent

More information

INFERENTIAL STATISTICS REVISION

INFERENTIAL STATISTICS REVISION INFERENTIAL STATISTICS REVISION PREMIUM VERSION PREVIEW WWW.MATHSPOINTS.IE/SIGN-UP/ 2016 LCHL Paper 2 Question 9 (a) (i) Data on earnings were published for a particular country. The data showed that the

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

CHAPTER 8. Personal Finance. Copyright 2015, 2011, 2007 Pearson Education, Inc. Section 8.4, Slide 1

CHAPTER 8. Personal Finance. Copyright 2015, 2011, 2007 Pearson Education, Inc. Section 8.4, Slide 1 CHAPTER 8 Personal Finance Copyright 2015, 2011, 2007 Pearson Education, Inc. Section 8.4, Slide 1 8.4 Compound Interest Copyright 2015, 2011, 2007 Pearson Education, Inc. Section 8.4, Slide 2 Objectives

More information

Review for Final Exam

Review for Final Exam Review for Final Exam Disclaimer: This review is more heavily weighted on Chapter 5 (finance), although some problems from other chapters will be included. Please also take a look at the previous Week

More information

Chapter 3. Lecture 3 Sections

Chapter 3. Lecture 3 Sections Chapter 3 Lecture 3 Sections 3.4 3.5 Measure of Position We would like to compare values from different data sets. We will introduce a z score or standard score. This measures how many standard deviation

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

Making Sense of Cents

Making Sense of Cents Name: Date: Making Sense of Cents Exploring the Central Limit Theorem Many of the variables that you have studied so far in this class have had a normal distribution. You have used a table of the normal

More information

Simple Interest. Compound Interest Start 10, , After 1 year 10, , After 2 years 11, ,449.00

Simple Interest. Compound Interest Start 10, , After 1 year 10, , After 2 years 11, ,449.00 Introduction We have all earned interest on money deposited in a savings account or paid interest on a credit card, but do you know how the interest was calculated? The two most common types of interest

More information

MA 1125 Lecture 14 - Expected Values. Wednesday, October 4, Objectives: Introduce expected values.

MA 1125 Lecture 14 - Expected Values. Wednesday, October 4, Objectives: Introduce expected values. MA 5 Lecture 4 - Expected Values Wednesday, October 4, 27 Objectives: Introduce expected values.. Means, Variances, and Standard Deviations of Probability Distributions Two classes ago, we computed the

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

The Central Limit Theorem. Sec. 8.2: The Random Variable. it s Distribution. it s Distribution

The Central Limit Theorem. Sec. 8.2: The Random Variable. it s Distribution. it s Distribution The Central Limit Theorem Sec. 8.1: The Random Variable it s Distribution Sec. 8.2: The Random Variable it s Distribution X p and and How Should You Think of a Random Variable? Imagine a bag with numbers

More information

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

6 Central Limit Theorem. (Chs 6.4, 6.5)

6 Central Limit Theorem. (Chs 6.4, 6.5) 6 Central Limit Theorem (Chs 6.4, 6.5) Motivating Example In the next few weeks, we will be focusing on making statistical inference about the true mean of a population by using sample datasets. Examples?

More information

L04: Homework Answer Key

L04: Homework Answer Key L04: Homework Answer Key Instructions: You are encouraged to collaborate with other students on the homework, but it is important that you do your own work. Before working with someone else on the assignment,

More information

Version A. Problem 1. Let X be the continuous random variable defined by the following pdf: 1 x/2 when 0 x 2, f(x) = 0 otherwise.

Version A. Problem 1. Let X be the continuous random variable defined by the following pdf: 1 x/2 when 0 x 2, f(x) = 0 otherwise. Math 224 Q Exam 3A Fall 217 Tues Dec 12 Version A Problem 1. Let X be the continuous random variable defined by the following pdf: { 1 x/2 when x 2, f(x) otherwise. (a) Compute the mean µ E[X]. E[X] x

More information

Fall 2011 Exam Score: /75. Exam 3

Fall 2011 Exam Score: /75. Exam 3 Math 12 Fall 2011 Name Exam Score: /75 Total Class Percent to Date Exam 3 For problems 1-10, circle the letter next to the response that best answers the question or completes the sentence. You do not

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

Since his score is positive, he s above average. Since his score is not close to zero, his score is unusual.

Since his score is positive, he s above average. Since his score is not close to zero, his score is unusual. Chapter 06: The Standard Deviation as a Ruler and the Normal Model This is the worst chapter title ever! This chapter is about the most important random variable distribution of them all the normal distribution.

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

Lecture 8. The Binomial Distribution. Binomial Distribution. Binomial Distribution. Probability Distributions: Normal and Binomial

Lecture 8. The Binomial Distribution. Binomial Distribution. Binomial Distribution. Probability Distributions: Normal and Binomial Lecture 8 The Binomial Distribution Probability Distributions: Normal and Binomial 1 2 Binomial Distribution >A binomial experiment possesses the following properties. The experiment consists of a fixed

More information

4.2 Probability Distributions

4.2 Probability Distributions 4.2 Probability Distributions Definition. A random variable is a variable whose value is a numerical outcome of a random phenomenon. The probability distribution of a random variable tells us what the

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

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

Random Variable: Definition

Random Variable: Definition Random Variables Random Variable: Definition A Random Variable is a numerical description of the outcome of an experiment Experiment Roll a die 10 times Inspect a shipment of 100 parts Open a gas station

More information

Midterm Test 1 (Sample) Student Name (PRINT):... Student Signature:... Use pencil, so that you can erase and rewrite if necessary.

Midterm Test 1 (Sample) Student Name (PRINT):... Student Signature:... Use pencil, so that you can erase and rewrite if necessary. MA 180/418 Midterm Test 1 (Sample) Student Name (PRINT):............................................. Student Signature:................................................... Use pencil, so that you can erase

More information

Class 11. Daniel B. Rowe, Ph.D. Department of Mathematics, Statistics, and Computer Science. Marquette University MATH 1700

Class 11. Daniel B. Rowe, Ph.D. Department of Mathematics, Statistics, and Computer Science. Marquette University MATH 1700 Class 11 Daniel B. Rowe, Ph.D. Department of Mathematics, Statistics, and Computer Science Copyright 2017 by D.B. Rowe 1 Agenda: Recap Chapter 5.3 continued Lecture 6.1-6.2 Go over Eam 2. 2 5: Probability

More information

Chapter 7: Random Variables

Chapter 7: Random Variables Chapter 7: Random Variables 7.1 Discrete and Continuous Random Variables 7.2 Means and Variances of Random Variables 1 Introduction A random variable is a function that associates a unique numerical value

More information

3 3 Measures of Central Tendency and Dispersion from grouped data.notebook October 23, 2017

3 3 Measures of Central Tendency and Dispersion from grouped data.notebook October 23, 2017 Warm Up a. Determine the sample standard deviation weight. Express your answer rounded to three decimal places. b. Use the Empirical Rule to determine the percentage of M&Ms with weights between 0.803

More information

Learning Plan 3 Chapter 3

Learning Plan 3 Chapter 3 Learning Plan 3 Chapter 3 Questions 1 and 2 (page 82) To convert a decimal into a percent, you must move the decimal point two places to the right. 0.72 = 72% 5.46 = 546% 3.0842 = 308.42% Question 3 Write

More information

MAT133Y5 Assignment 01

MAT133Y5 Assignment 01 Staple Here Score: / MAT133Y Assignment 01 Family Name: Given Name: Indicate the tutorial in which you are enrolled: TUT01 TUT02 TUT03 TUT04 TUT0 TUT08 T T1600 T00 W0900 W00 W10 TUT09 TUT0111 TUT0112 TUT0114

More information

Discrete Random Variables

Discrete Random Variables Discrete Random Variables MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2018 Objectives During this lesson we will learn to: distinguish between discrete and continuous

More information

Examples: Investments involving compound interest calculator)

Examples: Investments involving compound interest calculator) SINGLE PAYMENT Examples: Investments involving compound interest calculator) (ti 83 Future value calculations 1. $1200 is invested in a Canada Savings Bond at 4.6 % compounded annually for 6 years. What

More information

Discrete Random Variables

Discrete Random Variables Discrete Random Variables MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2017 Objectives During this lesson we will learn to: distinguish between discrete and continuous

More information

Graphing a Binomial Probability Distribution Histogram

Graphing a Binomial Probability Distribution Histogram Chapter 6 8A: Using a Normal Distribution to Approximate a Binomial Probability Distribution Graphing a Binomial Probability Distribution Histogram Lower and Upper Class Boundaries are used to graph the

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

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

Math 1324 Finite Mathematics Chapter 4 Finance

Math 1324 Finite Mathematics Chapter 4 Finance Math 1324 Finite Mathematics Chapter 4 Finance Simple Interest: Situation where interest is calculated on the original principal only. A = P(1 + rt) where A is I = Prt Ex: A bank pays simple interest at

More information

MA 1125 Lecture 12 - Mean and Standard Deviation for the Binomial Distribution. Objectives: Mean and standard deviation for the binomial distribution.

MA 1125 Lecture 12 - Mean and Standard Deviation for the Binomial Distribution. Objectives: Mean and standard deviation for the binomial distribution. MA 5 Lecture - Mean and Standard Deviation for the Binomial Distribution Friday, September 9, 07 Objectives: Mean and standard deviation for the binomial distribution.. Mean and Standard Deviation of the

More information

Math 14, Homework 7.1 p. 379 # 7, 9, 18, 20, 21, 23, 25, 26 Name

Math 14, Homework 7.1 p. 379 # 7, 9, 18, 20, 21, 23, 25, 26 Name 7.1 p. 379 # 7, 9, 18, 0, 1, 3, 5, 6 Name 7. Find each. (a) z α Step 1 Step Shade the desired percent under the mean statistics calculator to 99% confidence interval 3 1 0 1 3 µ 3σ µ σ µ σ µ µ+σ µ+σ µ+3σ

More information

Lecture Slides. Elementary Statistics Twelfth Edition. by Mario F. Triola. and the Triola Statistics Series. Section 7.4-1

Lecture Slides. Elementary Statistics Twelfth Edition. by Mario F. Triola. and the Triola Statistics Series. Section 7.4-1 Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series by Mario F. Triola Section 7.4-1 Chapter 7 Estimates and Sample Sizes 7-1 Review and Preview 7- Estimating a Population

More information

Discrete Probability Distribution

Discrete Probability Distribution 1 Discrete Probability Distribution Key Definitions Discrete Random Variable: Has a countable number of values. This means that each data point is distinct and separate. Continuous Random Variable: Has

More information

A random variable X is a function that assigns (real) numbers to the elements of the sample space S of a random experiment.

A random variable X is a function that assigns (real) numbers to the elements of the sample space S of a random experiment. RANDOM VARIABLES and PROBABILITY DISTRIBUTIONS A random variable X is a function that assigns (real) numbers to the elements of the samle sace S of a random exeriment. The value sace V of a random variable

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

6.1 Graphs of Normal Probability Distributions:

6.1 Graphs of Normal Probability Distributions: 6.1 Graphs of Normal Probability Distributions: Normal Distribution one of the most important examples of a continuous probability distribution, studied by Abraham de Moivre (1667 1754) and Carl Friedrich

More information

Module 4: Probability

Module 4: Probability Module 4: Probability 1 / 22 Probability concepts in statistical inference Probability is a way of quantifying uncertainty associated with random events and is the basis for statistical inference. Inference

More information

CH 6 Review Normal Probability Distributions College Statistics

CH 6 Review Normal Probability Distributions College Statistics CH 6 Review Normal Probability Distributions College Statistics Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Using the following uniform density

More information

Mr. Orchard s Math 141 WIR Final Exam Review Week 14

Mr. Orchard s Math 141 WIR Final Exam Review Week 14 1. A construction company has allocated $1.92 million to buy new bulldozers, backhoes, and dumptrucks. Bulldozers cost $16,000 each, backhoes cost $24,000 each, and dumptruckcs cost $32,000 each. The company

More information

WebAssign Math 3680 Homework 5 Devore Fall 2013 (Homework)

WebAssign Math 3680 Homework 5 Devore Fall 2013 (Homework) WebAssign Math 3680 Homework 5 Devore Fall 2013 (Homework) Current Score : 135.45 / 129 Due : Friday, October 11 2013 11:59 PM CDT Mirka Martinez Applied Statistics, Math 3680-Fall 2013, section 2, Fall

More information

Statistics for Business and Economics

Statistics for Business and Economics Statistics for Business and Economics Chapter 7 Estimation: Single Population Copyright 010 Pearson Education, Inc. Publishing as Prentice Hall Ch. 7-1 Confidence Intervals Contents of this chapter: Confidence

More information

6.2 Normal Distribution. Normal Distributions

6.2 Normal Distribution. Normal Distributions 6.2 Normal Distribution Normal Distributions 1 Homework Read Sec 6-1, and 6-2. Make sure you have a good feel for the normal curve. Do discussion question p302 2 3 Objective Identify Complete normal model

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. Assn.1-.3 Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) How long will it take for the value of an account to be $890 if $350 is deposited

More information

7.5 Amount of an Ordinary Annuity

7.5 Amount of an Ordinary Annuity 7.5 Amount of an Ordinary Annuity Nigel is saving $700 each year for a trip. Rashid is saving $200 at the end of each month for university. Jeanine is depositing $875 at the end of each 3 months for 3

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

Prob and Stats, Nov 7

Prob and Stats, Nov 7 Prob and Stats, Nov 7 The Standard Normal Distribution Book Sections: 7.1, 7.2 Essential Questions: What is the standard normal distribution, how is it related to all other normal distributions, and how

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

6. THE BINOMIAL DISTRIBUTION

6. THE BINOMIAL DISTRIBUTION 6. THE BINOMIAL DISTRIBUTION Eg: For 1000 borrowers in the lowest risk category (FICO score between 800 and 850), what is the probability that at least 250 of them will default on their loan (thereby rendering

More information

HSC Mathematics DUX. Sequences and Series Term 1 Week 4. Name. Class day and time. Teacher name...

HSC Mathematics DUX. Sequences and Series Term 1 Week 4. Name. Class day and time. Teacher name... DUX Phone: (02) 8007 6824 Email: info@dc.edu.au Web: dc.edu.au 2018 HIGHER SCHOOL CERTIFICATE COURSE MATERIALS HSC Mathematics Sequences and Series Term 1 Week 4 Name. Class day and time Teacher name...

More information

Statistics 6 th Edition

Statistics 6 th Edition Statistics 6 th Edition Chapter 5 Discrete Probability Distributions Chap 5-1 Definitions Random Variables Random Variables Discrete Random Variable Continuous Random Variable Ch. 5 Ch. 6 Chap 5-2 Discrete

More information

Estimation of the Mean and Proportion

Estimation of the Mean and Proportion Chapter 8 Estimation of the Mean and Proportion In statistics, we collect samples to know more about a population. If the sample is representative of the population, the sample mean or proportion should

More information

Examples: Random Variables. Discrete and Continuous Random Variables. Probability Distributions

Examples: Random Variables. Discrete and Continuous Random Variables. Probability Distributions Random Variables Examples: Random variable a variable (typically represented by x) that takes a numerical value by chance. Number of boys in a randomly selected family with three children. Possible values:

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

REAL LIFE PERCENT PRACTICE TEST

REAL LIFE PERCENT PRACTICE TEST Name ID DATE PERIOD REAL LIFE PERCENT PRACTICE TEST REMEMBER YOU CAN USE CALCULATORS BUT YOU MUST SHOW EACH SETUP!!!! 1. Find the sales tax to the nearest cent, then tell the cost with tax. A skateboard

More information

Tutorial 6. Sampling Distribution. ENGG2450A Tutors. 27 February The Chinese University of Hong Kong 1/6

Tutorial 6. Sampling Distribution. ENGG2450A Tutors. 27 February The Chinese University of Hong Kong 1/6 Tutorial 6 Sampling Distribution ENGG2450A Tutors The Chinese University of Hong Kong 27 February 2017 1/6 Random Sample and Sampling Distribution 2/6 Random sample Consider a random variable X with distribution

More information

Continuous Probability Distributions & Normal Distribution

Continuous Probability Distributions & Normal Distribution Mathematical Methods Units 3/4 Student Learning Plan Continuous Probability Distributions & Normal Distribution 7 lessons Notes: Students need practice in recognising whether a problem involves a discrete

More information

CHAPTER 6 Random Variables

CHAPTER 6 Random Variables CHAPTER 6 Random Variables 6.1 Discrete and Continuous Random Variables The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers Discrete and Continuous Random

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

Exponential Growth and Decay

Exponential Growth and Decay Exponential Growth and Decay Identifying Exponential Growth vs Decay A. Exponential Equation: f(x) = Ca x 1. C: COEFFICIENT 2. a: BASE 3. X: EXPONENT B. Exponential Growth 1. When the base is greater than

More information

Lecture 37 Sections 11.1, 11.2, Mon, Mar 31, Hampden-Sydney College. Independent Samples: Comparing Means. Robb T. Koether.

Lecture 37 Sections 11.1, 11.2, Mon, Mar 31, Hampden-Sydney College. Independent Samples: Comparing Means. Robb T. Koether. : : Lecture 37 Sections 11.1, 11.2, 11.4 Hampden-Sydney College Mon, Mar 31, 2008 Outline : 1 2 3 4 5 : When two samples are taken from two different populations, they may be taken independently or not

More information

Upcoming Schedule PSU Stat 2014

Upcoming Schedule PSU Stat 2014 Upcoming Schedule PSU Stat 014 Monday Tuesday Wednesday Thursday Friday Jan 6 Sec 7. Jan 7 Jan 8 Sec 7.3 Jan 9 Jan 10 Sec 7.4 Jan 13 Chapter 7 in a nutshell Jan 14 Jan 15 Chapter 7 test Jan 16 Jan 17 Final

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

Sec 5.2. Mean Variance Expectation. Bluman, Chapter 5 1

Sec 5.2. Mean Variance Expectation. Bluman, Chapter 5 1 Sec 5.2 Mean Variance Expectation Bluman, Chapter 5 1 Review: Do you remember the following? The symbols for Variance Standard deviation Mean The relationship between variance and standard deviation? Bluman,

More information

Statistics Class 15 3/21/2012

Statistics Class 15 3/21/2012 Statistics Class 15 3/21/2012 Quiz 1. Cans of regular Pepsi are labeled to indicate that they contain 12 oz. Data Set 17 in Appendix B lists measured amounts for a sample of Pepsi cans. The same statistics

More information

7-8 Exponential Growth and Decay Notes

7-8 Exponential Growth and Decay Notes 7-8 Eponential Growth and Decay Notes Decay y = a b where a > 0 and b is between 0 and 1 Eample : y = 100 (.5) As is increases by 1, y decreases to 1/2 of its previous value. Growth y = a b where a > 0

More information

LABOR FORCE STATUS OF THE CIVILIAN NONINSTITUTIONAL POPULATION RELEASE DATE: January 19, 2018 SEASONALLY ADJUSTED STATE OF FLORIDA UNITED STATES

LABOR FORCE STATUS OF THE CIVILIAN NONINSTITUTIONAL POPULATION RELEASE DATE: January 19, 2018 SEASONALLY ADJUSTED STATE OF FLORIDA UNITED STATES FORCE STATUS OF THE NONINSTITUTIONAL Over-the-Month Over-the-Year Current Month Month Ago Year Ago Change Change December November December Level Percent Level Percent STATE OF FLORIDA Population 16+ 17,070,000

More information

Chapter 2: Descriptive Statistics. Mean (Arithmetic Mean): Found by adding the data values and dividing the total by the number of data.

Chapter 2: Descriptive Statistics. Mean (Arithmetic Mean): Found by adding the data values and dividing the total by the number of data. -3: Measure of Central Tendency Chapter : Descriptive Statistics The value at the center or middle of a data set. It is a tool for analyzing data. Part 1: Basic concepts of Measures of Center Ex. Data

More information

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

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

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

Page Points Score Total: 100

Page Points Score Total: 100 Math 1130 Autumn 2018 Sample Midterm 2c 2/28/19 Name (Print): Username.#: Lecturer: Rec. Instructor: Rec. Time: This exam contains 8 pages (including this cover page) and 6 problems. Check to see if any

More information

Final Exam WIR Spring 2014

Final Exam WIR Spring 2014 Final Exam WIR Spring 2014 Disclaimer: This review is just a selection of good problems on the main topics in our course. It is absolutely NOT meant as a preview of the final exam or as a sample exam.

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

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

What type of distribution is this? tml

What type of distribution is this?  tml Warm Up Calculate the average Broncos score for the 2013 Season! 24, 27, 10, 10, 34, 37, 20, 51, 35, 31, 27, 28, 45, 33, 35, 52, 52, 37, 41, 49, 24, 26 What type of distribution is this? http://www.mathsisfun.com/data/quincunx.h

More information

CHAPTER 7 INTRODUCTION TO SAMPLING DISTRIBUTIONS

CHAPTER 7 INTRODUCTION TO SAMPLING DISTRIBUTIONS CHAPTER 7 INTRODUCTION TO SAMPLING DISTRIBUTIONS Note: This section uses session window commands instead of menu choices CENTRAL LIMIT THEOREM (SECTION 7.2 OF UNDERSTANDABLE STATISTICS) The Central Limit

More information

Central Limit Theorem

Central Limit Theorem Central Limit Theorem Lots of Samples 1 Homework Read Sec 6-5. Discussion Question pg 329 Do Ex 6-5 8-15 2 Objective Use the Central Limit Theorem to solve problems involving sample means 3 Sample Means

More information

11.5: Normal Distributions

11.5: Normal Distributions 11.5: Normal Distributions 11.5.1 Up to now, we ve dealt with discrete random variables, variables that take on only a finite (or countably infinite we didn t do these) number of values. A continuous random

More information

MTH 245: Mathematics for Management, Life, and Social Sciences

MTH 245: Mathematics for Management, Life, and Social Sciences 1/14 MTH 245: Mathematics for Management, Life, and Social Sciences Section 7.6 Section 7.6: The Normal Distribution. 2/14 The Normal Distribution. Figure: Abraham DeMoivre Section 7.6: The Normal Distribution.

More information

2. A loan of $7250 was repaid at the end of 8 months. What size repayment check was written if a 9% annual rate of interest was charged?

2. A loan of $7250 was repaid at the end of 8 months. What size repayment check was written if a 9% annual rate of interest was charged? Math 1630 Practice Test Name Chapter 5 Date For each problem, indicate which formula you are using, (B) substitute the given values into the appropriate places, and (C) solve the formula for the unknown

More information

Mathematical Methods: Practice Problem Solving Task - Probability

Mathematical Methods: Practice Problem Solving Task - Probability Mathematical Methods: Practice Problem Solving Task - Probability Question 1 refers to the following graph The following graph shows the probabilities of the 5 outcomes (1 to 5) from a spinner, with one

More information

Confidence Intervals. σ unknown, small samples The t-statistic /22

Confidence Intervals. σ unknown, small samples The t-statistic /22 Confidence Intervals σ unknown, small samples The t-statistic 1 /22 Homework Read Sec 7-3. Discussion Question pg 365 Do Ex 7-3 1-4, 6, 9, 12, 14, 15, 17 2/22 Objective find the confidence interval for

More information

EXPONENTIAL MODELS If quantity Q is known to increase/decrease by a fixed percentage p, in decimal form, then Q can be modeled by

EXPONENTIAL MODELS If quantity Q is known to increase/decrease by a fixed percentage p, in decimal form, then Q can be modeled by Name: Date: LESSON 4-7 MINDFUL MANIPULATION OF PERCENTS COMMON CORE ALGEBRA II Percents and phenomena that grow at a constant percent rate can be challenging, to say the least. This is due to the fact

More information

Honors Statistics. Daily Agenda

Honors Statistics. Daily Agenda Honors Statistics Aug 23-8:26 PM Daily Agenda Aug 23-8:31 PM 1 Write a program to generate random numbers. I've decided to give them free will. A Skip 4, 12, 16 Apr 25-10:55 AM Toss 4 times Suppose you

More information

Suppose you invest $ at 4% annual interest. How much will you have at the end of two years?

Suppose you invest $ at 4% annual interest. How much will you have at the end of two years? Example 1 Suppose you invest $1000.00 at 4% annual interest. How much will you have at the end of two years? Paul Koester () MA 111, Simple Interest September 19, 2011 1 / 13 Example 1 Suppose you invest

More information