LESSON 10: NORMAL DISTRIBUTION
|
|
- May Armstrong
- 6 years ago
- Views:
Transcription
1 LESSON 10: NORMAL DISTRIBUTION Outline Normal distribution Area under the curve, probability, percentile value Given z find area Given percentile value find z Given x find area Given percentile value find x 1 NORMAL DISTRIBUTION THE PROBABILITY DENSITY FUNCTION If a random variable X with mean µ and standard deviation σ is normally distributed, then its probability density function is given by f 1 σ ( 1/2 ) ( x µ ) ( x) = e σ 2π [ / ] 2 2 1
2 NORMAL DISTRIBUTION THE PROBABILITY DENSITY FUNCTION f (x ) Area under the curve = 1.00 f (x ) Mean, m=50 SD, s=10 Area between the vertical lines = P (40 X 60) x - VALUES 3 NORMAL DISTRIBUTION EFFECT OF CHANGING STANDARD DEVIATION SD,s=10 SD,s=15 SD,s=20 Mean,m= x-values 4 2
3 NORMAL DISTRIBUTION EFFECT OF CHANGING MEAN SD,s= x -values 5 f (x) Area under the curve = z -VALUES Mean=0 SD=1 6 3
4 Area = 1.00 Area = 0.50 Area = RELATIONSHIP BETWEEN x AND z If a random variable X is normally distributed with mean µ and standard deviation σ, then µ=50 σ=10 x µ z = σ or, x = µ + zσ z= x=
5 TABLE, z-values, AREA AND PROBABILITY Example 1.1: Table D, Appendix A, pp shows the area under the curve from Z=-8 to some z value. For example, the area from Z=-8 to Z= =1.34 is So, Φ 1.34 = , P Z 1.34 = P Z 1.34 = 0. ( ) ( ) ( ) TABLE, z-values, AREA AND PROBABILITY Example 1.2: The area shown on the table can be used to get many other areas. For example, using the fact that the area under the curve is 1.0, the area from Z=1.34 to Z= is = So, P( 1.34 Z ) = P( Z 1.34) =
6 TABLE, z-values, AREA AND PROBABILITY Example 1.3: The area shown on the table can be used to get area between any two z-values. For example, the area from z 1 =-1.25 to z 2 =1.34 is =0.8043, where is the area obtained from Table D for z 1 = So, P 1.25 Z 1.34 = 0. ( ) GIVEN z, FIND PROBABILITY Example 2: Find the following: 1. P 2. P 3. P 4. P ( Z 1.63) ( Z 1.63) ( 1.05 Z 1.63) ( 1.05 Z 1.63) 5. P 6. P ( Z < 1.63) ( Z = 1.63) 12 6
7 GIVEN z, FIND PROBABILITY : EXCEL Excel function NORMSDIST(z) provides the area under the standard normal distribution curve on the left side of z. Example: NORMSDIST(1.34) = = P Z 1.34 = Φ 1.34 ( ) ( ) P ( Z 1.34) =? Area =? To get the area on the left of Z = 1.34, F(1.34), use Excel function NORMSDIST(1.34). z= AREA AND PERCENTILE A percentile is the value at or below which the stated percentage of units lie. Therefore, percentile corresponds to an area under the curve. For example, if GMAT scores are normally distributed with the 78 th percentile 600, then 78% scores are less than 600 and P( X 600 ) = Then, the area on the left of X = 600 is If the 78 th percentile is 600, then the area on the left of X=600 is Area = 0.78 X=
8 GIVEN AREA OR PERCENTILE, FIND z Example 3: If return on investment of a fund has a mean 0 and standard deviation 1, find the returns that corresponds to following percentiles: th th 15 GIVEN AREA OR PERCENTILE, FIND z : EXCEL Excel function NORMSINV(p) provides the value of z corresponding to the 100p th percentile. For example, NORMSINV(0.33)= So, for the standard normal distribution, the 33 rd percentile is Area =0.33 z=? To get the z value for which area on the left, F(z) = 0.33, use Excel function NORMSINV(0.33). 16 8
9 NORMAL DISTRIBUTION GIVEN x, FIND PROBABILITY Example 4.1: A retailer has observed that the monthly demand of an item is normally distributed with a mean of 650 and standard deviation of 50 units. What is the probability that the demand of the item in the next month will not exceed 700 units? 1. Compute z P( X 700 ) =? 2. Find area from the Table 3. Find probability 17 Example 4.2: A retailer has observed that the monthly demand of an item is normally distributed with a mean of 650 and standard deviation of 50 units. What is the probability that the demand of the item in the next month will exceed 600 units? 1. Compute z NORMAL DISTRIBUTION GIVEN x, FIND PROBABILITY P( X 600 ) =? 2. Find area from the Table 3. Find probability 18 9
10 NORMAL DISTRIBUTION GIVEN x, FIND PROBABILITY Example 4.3: A retailer has observed that the monthly demand of an item is normally distributed with a mean of 650 and standard deviation of 50 units. What is the probability that the demand of the item in the next month will be between 600 and 700 units? 1. Compute z 1 and z P 2 ( 600 X 700) =? 2. Find areas from the Table 3. Find probability 19 NORMAL DISTRIBUTION GIVEN x, FIND PROBABILITY : EXCEL Excel function NORMDIST(x,µ,σ,TRUE) provides the area under the standard normal distribution curve on the left side of x. For example, NORMDIST(700,650,50,TRUE) = P( X 700 ) =? To get the area on the left of X = 700, when µ=600, s=50, use Excel function NORMSDIST(700,650,50,TRUE). Area=? µ=600 s=50 X =
11 NORMAL DISTRIBUTION GIVEN AREA OR PERCENTILE, FIND x Example 5: A retailer has observed that the monthly demand of an item is normally distributed with a mean of 650 and standard deviation of 50 units. If the retailer wants to meet demand with probability 0.90, how many units should be ordered for the next month? Assume that there is no units in the inventory. 1. Find z from the table 2. Find x 21 GIVEN AREA OR PERCENTILE, FIND x : EXCEL Excel function NORMINV(p,µ,σ) provides 100p th percentile when mean is µ and standard deviation σ. So, the function also gives that value of X for which the area on the left side of X is p. For example, NORMINV(0.90,650,50) = 714. So, the 90 th percentile is 714. To get the x value for which area on the left = 0.90, use Excel function NORMSINV(0.90,650,50) if mean is 650 and standard deviation 50. Area = 0.90 X =? µ=600 s=
12 READING AND EXERCISES Lesson 10 Reading: Section 7-4, pp Exercises: 7-35, 7-36,
BIOSTATISTICS. Lecture 3 Continuous Probability Distributions. dr. Petr Nazarov
Genomics Research Unit BIOSTATISTICS Lecture 3 Continuous Probability Distributions dr. Petr Nazarov 7-0-015 6-03-015 petr.nazarov@crp-sante.lu Lecture 3. Continuous probability distributions OUTLINE Lecture
More informationUsing Excel 2010 to Find Probabilities for the Normal and t Distributions
Using Excel 2010 to Find Probabilities for the Normal and t Distributions A TUTORIAL Using Excel with the Standard Normal, Normal, and t distributions Standard Normal ( Z ) Mean 0 Standard deviation 1
More informationThe Normal Distribution. The Gaussian Curve. Advantages of using Z-score. Importance of normal or Gaussian distribution (ND)
Importance of normal or Gaussian distribution (ND) The Normal It is the most used distribution Most method are based on the assumption of ND Sum of many independent, random contributions variables (grain
More informationNormal Curve in standard form: Answer each of the following questions
Basic Statistics Normal Curve in standard form: Answer each of the following questions What percent of the normal distribution lies between one and two standard deviations above the mean? What percent
More informationData Analysis. with Excel. An introduction for Physical scientists. LesKirkup university of Technology, Sydney CAMBRIDGE UNIVERSITY PRESS
Data Analysis with Excel An introduction for Physical scientists LesKirkup university of Technology, Sydney CAMBRIDGE UNIVERSITY PRESS Contents Preface xv 1 Introduction to scientific data analysis 1 1.1
More informationLecture 2. Estimating Single Population Parameters 8-1
Lecture 2 Estimating Single Population Parameters 8-1 8.1 Point and Confidence Interval Estimates for a Population Mean Point Estimate A single statistic, determined from a sample, that is used to estimate
More informationApplied Statistics and Probability for Engineers. Sixth Edition. Chapter 4 Continuous Random Variables and Probability Distributions.
Applied Statistics and Probability for Engineers Sixth Edition Douglas C. Montgomery George C. Runger Chapter 4 Continuous Random Variables and Probability Distributions 4 Continuous CHAPTER OUTLINE Random
More informationChapter 4 Continuous Random Variables and Probability Distributions
Applied Statistics and Probability for Engineers Sixth Edition Douglas C. Montgomery George C. Runger Chapter 4 Continuous Random Variables and Probability Distributions 4 Continuous CHAPTER OUTLINE 4-1
More information8: Statistical Distributions
: Statistical Distributions The Uniform Distribution 1 The Normal Distribution The Student Distribution Sample Calculations The Central Limit Theory Calculations with Samples Histograms & the Normal Distribution
More informationDensity Curves and the Normal Distributions. Histogram: 10 groups
Density Curves and the Normal Distributions MATH 2300 Chapter 6 Histogram: 10 groups 1 Histogram: 20 groups Histogram: 40 groups 2 Histogram: 80 groups Histogram: 160 groups 3 Density Curve Density Curves
More informationMAT 155. Key Concept. Density Curve
MAT 155 Dr. Claude Moore Cape Fear Community College Chapter 6 Normal Probability Distributions 6 1 Review and Preview 6 2 The Standard Normal Distribution 6 3 Applications of Normal Distributions 6 4
More informationNORMAL CURVE STANDARD SCORES AND THE NORMAL CURVE AREA UNDER THE NORMAL CURVE AREA UNDER THE NORMAL CURVE 9/11/2013
NORMAL CURVE AND THE NORMAL CURVE Prepared by: Jess Roel Q. Pesole Theoretical distribution of population scores represented by a bell-shaped curve obtained by a mathematical equation Used for: (1) Describing
More informationEQ: What is a normal distribution?
Unit 5 - Statistics What is the purpose EQ: What tools do we have to assess data? this unit? What vocab will I need? Vocabulary: normal distribution, standard, nonstandard, interquartile range, population
More informationFinal Exam Review (Math 1342)
Final Exam Review (Math 1342) 1) 5.5 5.7 5.8 5.9 6.1 6.1 6.3 6.4 6.5 6.6 6.7 6.7 6.7 6.9 7.0 7.0 7.0 7.1 7.2 7.2 7.4 7.5 7.7 7.7 7.8 8.0 8.1 8.1 8.3 8.7 Min = 5.5 Q 1 = 25th percentile = middle of first
More informationUnivariate Statistics. Z-Score
Univariate Statistics Z-Score The Sorted Score or Z-Score The standard score or z score of a data value gives the number of standard deviations that it differs from the mean. raw score mean z score = =
More informationMeasures of Location
Chapter 7 Measures of Location Definition of Measures of Location (page 219) A measure of location provides information on the percentage of observations in the collection whose values are less than or
More informationContinuous Probability Distributions
Continuous Probability Distributions Called a Probability density function. The probability is interpreted as "area under the curve." 1) The random variable takes on an infinite # of values within a given
More informationPossible Solutions for Homework #2 Econ B2000, MA Econometrics Kevin R Foster, CCNY
Possible Solutions f Homewk #2 Econ B2000, MA Econometrics Kevin R Foster, CCNY 1. Experiment with the file, samples_f_polls.xls, to create at least 100 polls, each with 30 people in it. Show a histogram
More information2011 Pearson Education, Inc
Statistics for Business and Economics Chapter 2 Methods for Describing Sets of Data Summary of Central Tendency Measures Measure Formula Description Mean x i / n Balance Point Median ( n +1) Middle Value
More informationNorm Referenced Test (NRT)
22 Norm Referenced Test (NRT) NRT Test Design In 2005, the MSA Mathematics tests included the TerraNova Mathematics Survey (TN) Form C at Grades 3, 4, 5, 7, and 8 and Form D at Grade 6. The MSA Grade 10
More informationMA Lesson 29 Notes
MA 15910 Lesson 9 Notes Absolute Maximums or Absolute Minimums (Absolute Extrema) in a Closed Interval: Let f be a continuous function on a closed interval [a, b].. Let c be a number in that interval.
More informationy = b x Exponential and Logarithmic Functions LESSON ONE - Exponential Functions Lesson Notes Example 1 Set-Builder Notation
y = b x Exponential and Logarithmic Functions LESSON ONE - Exponential Functions Example 1 Exponential Functions Graphing Exponential Functions For each exponential function: i) Complete the table of values
More informationMA 162: Finite Mathematics - Section 3.3/4.1
MA 162: Finite Mathematics - Section 3.3/4.1 Fall 2014 Ray Kremer University of Kentucky October 6, 2014 Announcements: Homework 3.3 due Tuesday at 6pm. Homework 4.1 due Friday at 6pm. Exam scores were
More informationBusiness Statistics. Lecture 3: Random Variables and the Normal Distribution
Business Statistics Lecture 3: Random Variables and the Normal Distribution 1 Goals for this Lecture A little bit of probability Random variables The normal distribution 2 Probability vs. Statistics Probability:
More informationIn this chapter, you will study the normal distribution, the standard normal, and applications associated with them.
The Normal Distribution The normal distribution is the most important of all the distributions. It is widely used and even more widely abused. Its graph is bell-shaped. You see the bell curve in almost
More information1 Continuous Probability Distributions
1 Continuous Probability Distributions 1.1 Normal Distribution Function 1.1.1 Exercise 1 Suppose that the amount of time to assemble a computer is normally distributed with a mean = 50 minutes and a standard
More informationSampling Distributions
Sampling and Variability Sampling Distributions Ken Kelley s Class Notes 1 / 44 Sampling and Variability Lesson Breakdown by Topic 1 Sampling and Variability Sampling/Variability Demonstration Standard
More informationChapter 4 - Lecture 3 The Normal Distribution
Chapter 4 - Lecture 3 The October 28th, 2009 Chapter 4 - Lecture 3 The Standard Chapter 4 - Lecture 3 The Standard Normal distribution is a statistical unicorn It is the most important distribution in
More informationBusiness Statistics. Chapter 6 Review of Normal Probability Distribution QMIS 220. Dr. Mohammad Zainal
Department of Quantitative Methods & Information Systems Business Statistics Chapter 6 Review of Normal Probability Distribution QMIS 220 Dr. Mohammad Zainal Chapter Goals After completing this chapter,
More informationChapter (7) Continuous Probability Distributions Examples Normal probability distribution
Chapter (7) Continuous robability Distributions Examples Normal probability distribution Example () How to find the area under the normal curve? If 50 Find & 6 60.8 50 X 60.8 6 0.8 p 6 0.5 0.464 0.964.8
More informationInverse Functions. Definition 1. The exponential function f with base a is denoted by. f(x) = a x
Inverse Functions Definition 1. The exponential function f with base a is denoted by f(x) = a x where a > 0, a 1, and x is any real number. Example 1. In the same coordinate plane, sketch the graph of
More informationExponential function and equations Exponential equations, logarithm, compound interest
Exercises 10 Exponential function and equations Exponential equations, logarithm, compound interest Objectives - be able to determine simple logarithms without a calculator. - be able to solve simple exponential
More information4.2 The Normal Distribution. that is, a graph of the measurement looks like the familiar symmetrical, bell-shaped
4.2 The Normal Distribution Many physiological and psychological measurements are normality distributed; that is, a graph of the measurement looks like the familiar symmetrical, bell-shaped distribution
More informationCORRELATION ANALYSIS. Dr. Anulawathie Menike Dept. of Economics
CORRELATION ANALYSIS Dr. Anulawathie Menike Dept. of Economics 1 What is Correlation The correlation is one of the most common and most useful statistics. It is a term used to describe the relationship
More informationLecture 10/Chapter 8 Bell-Shaped Curves & Other Shapes. From a Histogram to a Frequency Curve Standard Score Using Normal Table Empirical Rule
Lecture 10/Chapter 8 Bell-Shaped Curves & Other Shapes From a Histogram to a Frequency Curve Standard Score Using Normal Table Empirical Rule From Histogram to Normal Curve Start: sample of female hts
More informationEssential Question: What are the standard intervals for a normal distribution? How are these intervals used to solve problems?
Acquisition Lesson Planning Form Plan for the Concept, Topic, or Skill Normal Distributions Key Standards addressed in this Lesson: MM3D2 Time allotted for this Lesson: Standard: MM3D2 Students will solve
More information6.2 Area Under the Standard Normal Curve
6.2 Area Under the Standard Normal Curve Tom Lewis Fall Term 2009 Tom Lewis () 6.2 Area Under the Standard Normal Curve Fall Term 2009 1 / 6 Outline 1 The cumulative distribution function 2 The z α notation
More information7.1 Sampling Error The Need for Sampling Distributions
7.1 Sampling Error The Need for Sampling Distributions Tom Lewis Fall Term 2009 Tom Lewis () 7.1 Sampling Error The Need for Sampling Distributions Fall Term 2009 1 / 5 Outline 1 Tom Lewis () 7.1 Sampling
More informationSHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.
Math 1332 Exam Review Name SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. Find the cardinal number for the set. 1) {8, 10, 12,..., 66} 1) Are the sets
More informationExponential Functions
Exponential Functions MATH 160, Precalculus J. Robert Buchanan Department of Mathematics Fall 2011 Objectives In this lesson we will learn to: recognize and evaluate exponential functions with base a,
More information11/16/2017. Chapter. Copyright 2009 by The McGraw-Hill Companies, Inc. 7-2
7 Chapter Continuous Probability Distributions Describing a Continuous Distribution Uniform Continuous Distribution Normal Distribution Normal Approximation to the Binomial Normal Approximation to the
More information14.44/ Energy Economics, Spring 2006 Problem Set 2
14.44/14.444 Energy Economics, Spring 2006 Problem Set 2 Due Friday February 23, 2006 in class or Arthur Campbell s mail folder Late problem sets are not accepted This problem set reviews your knowledge
More informationNormal distributions
Normal distributions Suppose a region has area A and a subregion has area A 1 : If a point is placed at random in the larger region, the probability that the point is in the subregion is p = A1 A : If
More informationChapter 1 Linear Equations
. Lines. True. True. If the slope of a line is undefined, the line is vertical. 7. The point-slope form of the equation of a line x, y is with slope m containing the point ( ) y y = m ( x x ). Chapter
More informationEstadística I Exercises Chapter 4 Academic year 2015/16
Estadística I Exercises Chapter 4 Academic year 2015/16 1. An urn contains 15 balls numbered from 2 to 16. One ball is drawn at random and its number is reported. (a) Define the following events by listing
More informationWriting and Graphing Inequalities
4.1 Writing and Graphing Inequalities solutions of an inequality? How can you use a number line to represent 1 ACTIVITY: Understanding Inequality Statements Work with a partner. Read the statement. Circle
More informationSection 5.1: Probability and area
Section 5.1: Probability and area Review Normal Distribution s z = x - m s Standard Normal Distribution s=1 m x m=0 z The area that falls in the interval under the nonstandard normal curve is the same
More informationGrade 10 Academic Math (MPM2D0) Integer Skills Summer Package. Table of Contents
Grade 10 Academic Math (MPM2D0) Integer Skills Summer Package Table of Contents Content Pages 1) Adding Integers: Skills Practice and Practice 1-2 2) Subtracting Integers: Skills Practice and Practice
More informationSections 6.1 and 6.2: The Normal Distribution and its Applications
Sections 6.1 and 6.2: The Normal Distribution and its Applications Definition: A normal distribution is a continuous, symmetric, bell-shaped distribution of a variable. The equation for the normal distribution
More informationSlide 1. Slide 2. Slide 3. Pick a Brick. Daphne. 400 pts 200 pts 300 pts 500 pts 100 pts. 300 pts. 300 pts 400 pts 100 pts 400 pts.
Slide 1 Slide 2 Daphne Phillip Kathy Slide 3 Pick a Brick 100 pts 200 pts 500 pts 300 pts 400 pts 200 pts 300 pts 500 pts 100 pts 300 pts 400 pts 100 pts 400 pts 100 pts 200 pts 500 pts 100 pts 400 pts
More informationContinuous Probability Distributions
1 Chapter 5 Continuous Probability Distributions 5.1 Probability density function Example 5.1.1. Revisit Example 3.1.1. 11 12 13 14 15 16 21 22 23 24 25 26 S = 31 32 33 34 35 36 41 42 43 44 45 46 (5.1.1)
More informationChapter 6 The Normal Distribution
Chapter 6 The Normal PSY 395 Oswald Outline s and area The normal distribution The standard normal distribution Setting probable limits on a score/observation Measures related to 2 s and Area The idea
More informationIndex. Cambridge University Press Data Analysis for Physical Scientists: Featuring Excel Les Kirkup Index More information
χ 2 distribution, 410 χ 2 test, 410, 412 degrees of freedom, 414 accuracy, 176 adjusted coefficient of multiple determination, 323 AIC, 324 Akaike s Information Criterion, 324 correction for small data
More informationZ score indicates how far a raw score deviates from the sample mean in SD units. score Mean % Lower Bound
1 EDUR 8131 Chat 3 Notes 2 Normal Distribution and Standard Scores Questions Standard Scores: Z score Z = (X M) / SD Z = deviation score divided by standard deviation Z score indicates how far a raw score
More informationMS-E2140. Lecture 1. (course book chapters )
Linear Programming MS-E2140 Motivations and background Lecture 1 (course book chapters 1.1-1.4) Linear programming problems and examples Problem manipulations and standard form Graphical representation
More informationVariables. Lecture 12 Sections Tue, Feb 3, Hampden-Sydney College. Displaying Distributions - Qualitative.
Lecture 12 Sections 4.3.1-4.3.2 Hampden-Sydney College Tue, Feb 3, 2008 Outline 1 2 3 4 5 Exercise 4.2, p. 219 Determine whether the following variables are qualitative, quantitative discrete, or quantitative
More informationMS-E2140. Lecture 1. (course book chapters )
Linear Programming MS-E2140 Motivations and background Lecture 1 (course book chapters 1.1-1.4) Linear programming problems and examples Problem manipulations and standard form problems Graphical representation
More information6. 5x Division Property. CHAPTER 2 Linear Models, Equations, and Inequalities. Toolbox Exercises. 1. 3x = 6 Division Property
CHAPTER Linear Models, Equations, and Inequalities CHAPTER Linear Models, Equations, and Inequalities Toolbox Exercises. x = 6 Division Property x 6 = x =. x 7= Addition Property x 7= x 7+ 7= + 7 x = 8.
More informationLast Lecture. Distinguish Populations from Samples. Knowing different Sampling Techniques. Distinguish Parameters from Statistics
Last Lecture Distinguish Populations from Samples Importance of identifying a population and well chosen sample Knowing different Sampling Techniques Distinguish Parameters from Statistics Knowing different
More informationUNIT 14 AREA PROPERTY OF NORMAL DISTRIBUTION
UNIT 4 AREA PROPERTY OF NORMAL DISTRIBUTION Area Property of Normal Distribution Structure 4. Introduction Objectives 4. Area Property of Normal Distribution 4.3 Fitting of Normal Curve using Area Property
More informationIntroduction to Probability and Statistics Twelfth Edition
Introduction to Probability and Statistics Twelfth Edition Robert J. Beaver Barbara M. Beaver William Mendenhall Presentation designed and written by: Barbara M. Beaver Introduction to Probability and
More informationHYPOTHESIS TESTING. Hypothesis Testing
MBA 605 Business Analytics Don Conant, PhD. HYPOTHESIS TESTING Hypothesis testing involves making inferences about the nature of the population on the basis of observations of a sample drawn from the population.
More informationQuestion. z-scores. What We Will Cover in This Section. On which of the following tests did Pat do best compared to the other students?
z-scores 9/17/2003 P225 Z-scores 1 What We Will Cover in This Section What a z-score is. Computation. Properties. Assumptions. Uses 9/17/2003 P225 Z-scores 2 Question On which of the following tests did
More informationCalculation exercise 1 MRP, JIT, TOC and SOP. Dr Jussi Heikkilä
Calculation exercise 1 MRP, JIT, TOC and SOP Dr Jussi Heikkilä Problem 1: MRP in XYZ Company fixed lot size Item A Period 1 2 3 4 5 6 7 8 9 10 Gross requirements 71 46 49 55 52 47 51 48 56 51 Scheduled
More information3E4: Modelling Choice
3E4: Modelling Choice Lecture 6 Goal Programming Multiple Objective Optimisation Portfolio Optimisation Announcements Supervision 2 To be held by the end of next week Present your solutions to all Lecture
More informationChapter (7) Continuous Probability Distributions Examples
Chapter (7) Continuous Probability Distributions Examples The uniform distribution Example () Australian sheepdogs have a relatively short life.the length of their life follows a uniform distribution between
More informationSTATISTICS/MATH /1760 SHANNON MYERS
STATISTICS/MATH 103 11/1760 SHANNON MYERS π 100 POINTS POSSIBLE π YOUR WORK MUST SUPPORT YOUR ANSWER FOR FULL CREDIT TO BE AWARDED π YOU MAY USE A SCIENTIFIC AND/OR A TI-83/84/85/86 CALCULATOR ONCE YOU
More informationSpecial distributions
Special distributions August 22, 2017 STAT 101 Class 4 Slide 1 Outline of Topics 1 Motivation 2 Bernoulli and binomial 3 Poisson 4 Uniform 5 Exponential 6 Normal STAT 101 Class 4 Slide 2 What distributions
More informationMath 1314 Test 2 Review Lessons 2 8
Math 1314 Test Review Lessons 8 CASA reservation required. GGB will be provided on the CASA computers. 50 minute exam. 15 multiple choice questions. Do Practice Test for extra practice and extra credit.
More informationLecture # 31. Questions of Marks 3. Question: Solution:
Lecture # 31 Given XY = 400, X = 5, Y = 4, S = 4, S = 3, n = 15. Compute the coefficient of correlation between XX and YY. r =0.55 X Y Determine whether two variables XX and YY are correlated or uncorrelated
More informationAnalytics for an Online Retailer: Demand Forecasting and Price Optimization
Analytics for an Online Retailer: Demand Forecasting and Price Optimization Kris Johnson Ferreira Technology and Operations Management Unit, Harvard Business School, kferreira@hbs.edu Bin Hong Alex Lee
More informationISyE 6201: Manufacturing Systems Instructor: Spyros Reveliotis Spring 2006 Solutions to Homework 1
ISyE 601: Manufacturing Systems Instructor: Spyros Reveliotis Spring 006 Solutions to Homework 1 A. Chapter, Problem 4. (a) D = 60 units/wk 5 wk/yr = 310 units/yr h = ic = 0.5/yr $0.0 = $0.005/ yr A =
More informationvalue mean standard deviation
Mr. Murphy AP Statistics 2.4 The Empirical Rule and z - Scores HW Pg. 208 #4.45 (a) - (c), 4.46, 4.51, 4.52, 4.73 Objectives: 1. Calculate a z score. 2. Apply the Empirical Rule when appropriate. 3. Calculate
More informationEXPONENTIAL, LOGARITHMIC, AND TRIGONOMETRIC FUNCTIONS
Calculus for the Life Sciences nd Edition Greenwell SOLUTIONS MANUAL Full download at: https://testbankreal.com/download/calculus-for-the-life-sciences-nd-editiongreenwell-solutions-manual-/ Calculus for
More informationMath 2311 Sections 4.1, 4.2 and 4.3
Math 2311 Sections 4.1, 4.2 and 4.3 4.1 - Density Curves What do we know about density curves? Example: Suppose we have a density curve defined for defined by the line y = x. Sketch: What percent of observations
More informationIdentify the scale of measurement most appropriate for each of the following variables. (Use A = nominal, B = ordinal, C = interval, D = ratio.
Answers to Items from Problem Set 1 Item 1 Identify the scale of measurement most appropriate for each of the following variables. (Use A = nominal, B = ordinal, C = interval, D = ratio.) a. response latency
More informationReview. Midterm Exam. Midterm Review. May 6th, 2015 AMS-UCSC. Spring Session 1 (Midterm Review) AMS-5 May 6th, / 24
Midterm Exam Midterm Review AMS-UCSC May 6th, 2015 Spring 2015. Session 1 (Midterm Review) AMS-5 May 6th, 2015 1 / 24 Topics Topics We will talk about... 1 Review Spring 2015. Session 1 (Midterm Review)
More informationThe Normal Distribuions
The Normal Distribuions Sections 5.4 & 5.5 Cathy Poliak, Ph.D. cathy@math.uh.edu Office in Fleming 11c Department of Mathematics University of Houston Lecture 15-3339 Cathy Poliak, Ph.D. cathy@math.uh.edu
More informationLecture 10: The Normal Distribution. So far all the random variables have been discrete.
Lecture 10: The Normal Distribution 1. Continuous Random Variables So far all the random variables have been discrete. We need a different type of model (called a probability density function) for continuous
More informationEngage NY MODULE 3 LESSON 2: GENERATING EQUIVALENT EXPRESSIONS
Engage NY MODULE 3 LESSON 2: GENERATING EQUIVALENT EXPRESSIONS "Grade 7 Mathematics Module 3." Grade 7 Mathematics Module 3. 9 Sept. 2014. Web. 26 Jan. 2015. .
More informationDemand Estimation Sub-Committee MOD330 Phase 1 and 2. 7 th November 2012
Demand Estimation Sub-Committee MOD330 Phase 1 and 2 7 th November 2012 DESC: Phase 1 Update (1 of 2) 2 Teleconference took place on 18 th October to obtain DESC confirmation of scope of weather data requirements
More information6 THE NORMAL DISTRIBUTION
CHAPTER 6 THE NORMAL DISTRIBUTION 341 6 THE NORMAL DISTRIBUTION Figure 6.1 If you ask enough people about their shoe size, you will find that your graphed data is shaped like a bell curve and can be described
More informationAnswers Part A. P(x = 67) = 0, because x is a continuous random variable. 2. Find the following probabilities:
Answers Part A 1. Woman s heights are normally distributed with a mean of 63.6 inches and a standard deviation of 2.5 inches. Find the probability that a single randomly selected woman will be 67 inches
More informationLesson 9: Examples of Functions from Geometry
Lesson 9: Examples of Functions from Geometry Classwork Exercises As you complete Exercises 1 4, record the information in the table below. Side length (s) Area (A) Expression that describes area of border
More informationBiostatistics in Dentistry
Biostatistics in Dentistry Continuous probability distributions Continuous probability distributions Continuous data are data that can take on an infinite number of values between any two points. Examples
More informationHomework Exercises. 1. You want to conduct a test of significance for p the population proportion.
Homework Exercises 1. You want to conduct a test of significance for p the population proportion. The test you will run is H 0 : p = 0.4 Ha: p > 0.4, n = 80. you decide that the critical value will be
More informationDemand Forecasting. for. Microsoft Dynamics 365 for Operations. User Guide. Release 7.1. April 2018
Demand Forecasting for Microsoft Dynamics 365 for Operations User Guide Release 7.1 April 2018 2018 Farsight Solutions Limited All Rights Reserved. Portions copyright Business Forecast Systems, Inc. This
More informationRATING TRANSITIONS AND DEFAULT RATES
RATING TRANSITIONS AND DEFAULT RATES 2001-2012 I. Transition Rates for Banks Transition matrices or credit migration matrices characterise the evolution of credit quality for issuers with the same approximate
More informationQuality Measures (QM) Report. Self Guided Tutorial
Quality Measures (QM) Report Self Guided Tutorial 1 Tutorial Contents Overview of the QM Online Report Facility Summary Report Resident Drill down Monthly Trend Report Resident Roster Report Printing Reports/Export
More informationC.3 First-Order Linear Differential Equations
A34 APPENDIX C Differential Equations C.3 First-Order Linear Differential Equations Solve first-order linear differential equations. Use first-order linear differential equations to model and solve real-life
More informationProbability Distribution for a normal random variable x:
Chapter5 Continuous Random Variables 5.3 The Normal Distribution Probability Distribution for a normal random variable x: 1. It is and about its mean µ. 2. (the that x falls in the interval a < x < b is
More informationSTATISTICS INDEX NUMBER
NAME SCHOOL INDEX NUMBER DATE STATISTICS KCSE 1989 2012 Form 4 Mathematics Answer all the questions 1. 1989 Q12 P1 The table below shows the defective bolts from 40 samples No. of detective 0 1 2 3 4 5
More informationThe Normal Distribution. Chapter 6
+ The Normal Distribution Chapter 6 + Applications of the Normal Distribution Section 6-2 + The Standard Normal Distribution and Practical Applications! We can convert any variable that in normally distributed
More informationCollege Algebra. Word Problems
College Algebra Word Problems Example 2 (Section P6) The table shows the numbers N (in millions) of subscribers to a cellular telecommunication service in the United States from 2001 through 2010, where
More informationForecasting. Chapter Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
Forecasting Chapter 15 15-1 Chapter Topics Forecasting Components Time Series Methods Forecast Accuracy Time Series Forecasting Using Excel Time Series Forecasting Using QM for Windows Regression Methods
More information2/23/2015 GEOGRAPHY 204: STATISTICAL PROBLEM SOLVING IN GEOGRAPHY THE NORMAL DISTRIBUTION THE NORMAL DISTRIBUTION
Fall 2015: Lembo GEOGRAPHY 204: STATISTICAL PROBLEM SOLVING IN GEOGRAPHY Most generally applied probability distribution Enables assumptions about data properties Basis for sampling theory and statistical
More informationequal to the of the. Sample variance: Population variance: **The sample variance is an unbiased estimator of the
DEFINITION The variance (aka dispersion aka spread) of a set of values is a measure of equal to the of the. Sample variance: s Population variance: **The sample variance is an unbiased estimator of the
More informationMidrange: mean of highest and lowest scores. easy to compute, rough estimate, rarely used
Measures of Central Tendency Mode: most frequent score. best average for nominal data sometimes none or multiple modes in a sample bimodal or multimodal distributions indicate several groups included in
More informationPre-Calculus Multiple Choice Questions - Chapter S8
1 If every man married a women who was exactly 3 years younger than he, what would be the correlation between the ages of married men and women? a Somewhat negative b 0 c Somewhat positive d Nearly 1 e
More informationBUSI 460 Suggested Answers to Selected Review and Discussion Questions Lesson 7
BUSI 460 Suggested Answers to Selected Review and Discussion Questions Lesson 7 1. The definitions follow: (a) Time series: Time series data, also known as a data series, consists of observations on a
More information