C 1 C 2 C i C n C 1 C 2. C i. C n


 Natalie Short
 1 years ago
 Views:
Transcription
1 Exercises 1. A microcomputer system consists of a microprocessor CPU chip and a random access memory chip. The CPU is selected from a lot of 100 of which 10 are defective and the memory chip is selected fro a lot of 300 of which 15 are defective. Define A to be the event the selected CPU chip is defective and B the selected memory chip is defective. Since the two chips are selected from different lots, we may expect the events A and B to be independent. Could you check that? 2. There are 4 nonconforming capacitors in a lot of 25. A sample of 6 capacitors is taken. What is the probability of finding 2 nonconforming capacitors in the sample? Also find the mean and the standard deviation. 3. A random sample of 5 shafts is chosen from a Normal population with a mean diameter of 45mm and standard deviation 0.2mm. What is the probability that the mean diameter of a sample is less than 44.92mm? 4. The difference in the proportion of nonconforming components produced by 2 processes is to be established. A random sample of 96 parts taken from one process produced 6 non conforming parts and a sample of 120 parts taken from the second process had 8 nonconforming parts. Find the 95% confidence interval for the difference in proportion of non conforming parts. 5. A random sample of 12 silicon wafers has an average thickness of270µm. The standard deviation is known to be 8µm. Determine a twosided 99% CI interval for the thickness mean. 6. A random sample of 140 silicon wafers has 12 nonconforming units. Estimate the process fraction that are nonconforming and construct a two sided 95% CI for the true proportion that are non conforming. 7. A experiment is set up as H 0 : µ = µ 0, H 1 : µ µ 0 and is tested at a level of significance of 0.1. The sample size is 15. Determine the probability of rejecting H 0 if the true µ has shifted 0.25 standard deviation to the right of µ A system is made up of n independent components with reliability (Probability of working correctly) R i for the component C i. We will assume that failure events of components are mutually independent. Several organizations are possible : (a) A series system is one in which all components are so interrelated that the entire system will fail if any one of its components fails. Compute the reliabilty of a series system. 1
2 (b) On the other hand, a parallel system is one that will fail only if all its components fail (parallel redundancy). Compute the reliability of a parallel system. The following pictures describe respectively a series system and a parallel system. C 1 C 2 C i C n C 1 C 2 C i C n (c) Partial redundancy systems : the system has n components, each of them with a reliability R but the systems works if at least k components among n are working. Compute the reliability of such a system. 2
3 9. Let a telecommunication network linking different cities : V 2 V 3 V 1 V 6 V 4 V 5 Let R be the probability of success (no failure) of an interconnection (duplex link). We suppose that 2 cities V i and V j are connected if there is at least one path linking V i à V j with all its interconnections working. a) Give the probability that V 2 and V 6 can communicate correctly. Application for R = 0.99 (= ). b) Study the problem for V 1 and V 6. Solve this problem with conditional probabilities. Application for R = The following system is working if there is at least one working path from A to B. A C 1 C 2 C 4 B C 3 C 5 X i = C i is working ; R i = P(X i ) X = the system is working ; R = P(X) Compute R. 3
4 11. A transistor failure is modeled using a constant failure rate of per hour. Find the reliability of the transistor after 6000 hours of operation. Also determine the MTTF(Mean Time to Failure). 12. If a product reliability of 0.9 is to be achieved after 8000 hours of operation, determine the failure rate assuming an exponential distribution. 13. The life (hours) of a component is modeled using lognormal distribution. The 2 parameters for the distribution is given as mean µ = 5.5 and standard deviation σ = 1.6 Detremine the reliability of the component at 1000 hours and its MTTF. 14. A television camera focus system has 8 components in series. Each component failure has an exponential distribution with a failure rate of 40 per 10 6 hours. Determine the reliability at the end of 5000 hours of operation. Also calculate the MTTF for the system. If a reliability of 0.95 is desired after 5000 hours for the television camera, what should be the failure rate for each component? 15. A system has 3 components connected in parallel. The reliabilities of the components are 0.92,0.88 and 0.95 respectively. Determine the system reliability. If these reliabilities are at time 2000 hours of operation what is the MTTF of the system? (Assume exponential distribution for reliabilities) 16. A system has 5 components with system success defined as 4 out of 5. The reliability of each component is R = 0.9 at time T = 1. Detremine the system reliability and the MTTF. 17. A system has one basic unit and 2 standby units. The failure rate for each component is per hour. Find the system reliability at 400 hours of operation. Also determine the MTTF of the system. 18. A population of components is decribed by its life distribution (in hours) F(t) = 1 + ( t) 1 What is the probability that a new unit will fail by 1000 hours? by 4000 hours? between 1000 and 4000 hours? What proportion of these components will last more than 9000 hours? If we use 150 of them, how many do we expect to fail in the first 1000 hours?in the next 3000 hours? Derive the failure rate and calculate it at 10,100, 1000 and hours. Give the last failure rate in both PPM/K(per million per thousand hours) 19. The company Lifetime light bulb makes an incandescent filament that they believe does not wear out during an extended period of 4
5 normal use. They want w to guarantee it for 10 years of operation. To estimate the cost of such a guarantee, the Quality Departement takes a sample of 100 and realizes some accelerated tests (they have been given 3 months for that). Fortunately, the engineer who has to come with a test plan has a verified way of stressing light bulbs (using higher than normal voltages) which can simulate a month of typical use by a buyer in 1 hour of laboratory testing. He is able to take a random sample of 100 bulbs and test them all until failure in less than 3 months. The test engineer wants to use an exponential distribution for its bulbs failures based on his past experience. The sample data are the following : We have grouped the data in classes : lifetime in hours frequency plus de 440h 4 (a) Draw the histogram of the distribution. (b) Give the mode, the median, 1st and 3rd quartiles. (c) We suppose that the underlying distribution is exponential with parameter λ. Estimate the MTTF and λ. (d) Find a 95% CI interval for the true mean of the distribution. (e) Give an estimate of the reliability at 10 years. 5
6 (f) You want to check if the distribution is really exponential by performing a test. Give the hypothesis and perform a goodness of fit test. 20. The following data were collected in a test and are used to attempt a lognormal fit. The sample size is 15. Determine the lognormal parameters. The failure times in hours are 37.2, 39.2, 50.3, 52.6, 54.2, 66.0, 67.6, 70.9, 99.6, 106.5, 114.6, 128.7, 141.6, 197.3, A failure terminated test was performed on 15 gyro units without replacement. The test was terminated after 5 failures. The failure times in hours are 642,674,705,722, 732. Determine the 95% CI for the mean life using the exponential timetofailure model. 6
Practice Exam. 1. What is the median of this data? A) 64 B) 63.5 C) 67.5 D) 59 E) 35
Practice Exam Use the following to answer questions 12: A census is done in a given region. Following are the populations of the towns in that particular region (in thousands): 35, 46, 52, 63, 64, 71,
More informationFINAL EXAM REVIEW  Fa 13
FINAL EXAM REVIEW  Fa 13 Determine which of the four levels of measurement (nominal, ordinal, interval, ratio) is most appropriate. 1) The temperatures of eight different plastic spheres. 2) The sample
More informationStatistics  Written Examination MEC Students  BOVISA
Statistics  Written Examination MEC Students  BOVISA Prof.ssa A. Guglielmi 26.0.2 All rights reserved. Legal action will be taken against infringement. Reproduction is prohibited without prior consent.
More informationReliability Prediction Basics
Reliability Prediction Basics Reliability predictions are one of the most common forms of reliability analysis. Reliability predictions predict the failure rate of components and overall system reliability.
More informationConstruct a scatterplot for the given data. 2) x Answer:
Review for Test 5 STA 2023 spr 2014 Name Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents
More informationProb & Stats. Chapter 9 Review
Chapter 9 Review Construct the indicated confidence interval for the difference between the two population means. Assume that the two samples are independent simple random samples selected from normally
More informationThese help quantify the quality of a design from different perspectives: Cost Functionality Robustness Performance Energy consumption
Basic Properties of a Digital Design These help quantify the quality of a design from different perspectives: Cost Functionality Robustness Performance Energy consumption Which of these criteria is important
More informationStatistics 641  EXAM II  1999 through 2003
Statistics 641  EXAM II  1999 through 2003 December 1, 1999 I. (40 points ) Place the letter of the best answer in the blank to the left of each question. (1) In testing H 0 : µ 5 vs H 1 : µ > 5, the
More informationPreliminary Evaluation of Data Retention Characteristics for Ferroelectric Random Access Memories (FRAMs).
1 Preliminary Evaluation of Data Retention Characteristics for Ferroelectric Random Access Memories (FRAMs). 1.0 Introduction 1.1 FRAM Technology Background Ashok K. Sharma/NASA Ashok.k.Sharma.1@gsfc.nasa.gov
More informationStatistics I for QBIC. Contents and Objectives. Chapters 1 7. Revised: August 2013
Statistics I for QBIC Text Book: Biostatistics, 10 th edition, by Daniel & Cross Contents and Objectives Chapters 1 7 Revised: August 2013 Chapter 1: Nature of Statistics (sections 1.11.6) Objectives
More informationPower and Sample Size Determination
Power and Sample Size Determination Bret Hanlon and Bret Larget Department of Statistics University of Wisconsin Madison November 3 8, 2011 Power 1 / 31 Experimental Design To this point in the semester,
More informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
STATISTICS/GRACEY EXAM 3 PRACTICE/CH. 89 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the Pvalue for the indicated hypothesis test. 1) A
More informationCHAPTER 86 MEAN, MEDIAN, MODE AND STANDARD DEVIATION
CHAPTER 86 MEAN, MEDIAN, MODE AND STANDARD DEVIATION EXERCISE 36 Page 919 1. Determine the mean, median and modal values for the set: {3, 8, 10, 7, 5, 14,, 9, 8} Mean = 3+ 8 + 10 + 7 + 5 + 14 + + 9 + 8
More informationStandard Deviation Calculator
CSS.com Chapter 35 Standard Deviation Calculator Introduction The is a tool to calculate the standard deviation from the data, the standard error, the range, percentiles, the COV, confidence limits, or
More informationSTATISTICAL QUALITY CONTROL (SQC)
Statistical Quality Control 1 SQC consists of two major areas: STATISTICAL QUALITY CONTOL (SQC)  Acceptance Sampling  Process Control or Control Charts Both of these statistical techniques may be applied
More informationChapter 8: Introduction to Hypothesis Testing
Chapter 8: Introduction to Hypothesis Testing We re now at the point where we can discuss the logic of hypothesis testing. This procedure will underlie the statistical analyses that we ll use for the remainder
More informationTutor/(or Student) Guide to: Tutorled Tutorials
Tutor/(or Student) Guide to: Tutorled Tutorials (Module Code: Stat10050) Tutor Name: Module Coordinator: Dr. Patrick Murphy Description of Tutorials Introduction to Statistical Modelling Tutorials: Aim
More informationConfidence Intervals for Cp
Chapter 296 Confidence Intervals for Cp Introduction This routine calculates the sample size needed to obtain a specified width of a Cp confidence interval at a stated confidence level. Cp is a process
More informationConfidence Intervals for One Standard Deviation Using Standard Deviation
Chapter 640 Confidence Intervals for One Standard Deviation Using Standard Deviation Introduction This routine calculates the sample size necessary to achieve a specified interval width or distance from
More informationThe purpose of this procedure is to document the process for generating Reliability Block Diagram (RBD) for Sydney Water s facility assets.
Procedure Reliability Block Diagram (RBD). Overview.. Objective The purpose of this procedure is to document the process for generating Reliability Block Diagram (RBD) for Sydney Water s facility assets..2.
More informationStatistical Inference
Statistical Inference Idea: Estimate parameters of the population distribution using data. How: Use the sampling distribution of sample statistics and methods based on what would happen if we used this
More informationChapter 10. Verification and Validation of Simulation Models Prof. Dr. Mesut Güneş Ch. 10 Verification and Validation of Simulation Models
Chapter 10 Verification and Validation of Simulation Models 10.1 Contents ModelBuilding, Verification, and Validation Verification of Simulation Models Calibration and Validation 10.2 Purpose & Overview
More informationCents and the Central Limit Theorem Overview of Lesson GAISE Components Common Core State Standards for Mathematical Practice
Cents and the Central Limit Theorem Overview of Lesson In this lesson, students conduct a handson demonstration of the Central Limit Theorem. They construct a distribution of a population and then construct
More information93.4 Likelihood ratio test. NeymanPearson lemma
93.4 Likelihood ratio test NeymanPearson lemma 91 Hypothesis Testing 91.1 Statistical Hypotheses Statistical hypothesis testing and confidence interval estimation of parameters are the fundamental
More informationSample Exam #1 Elementary Statistics
Sample Exam #1 Elementary Statistics Instructions. No books, notes, or calculators are allowed. 1. Some variables that were recorded while studying diets of sharks are given below. Which of the variables
More informationChapter 14: 16, 9, 12; Chapter 15: 8 Solutions When is it appropriate to use the normal approximation to the binomial distribution?
Chapter 14: 16, 9, 1; Chapter 15: 8 Solutions 141 When is it appropriate to use the normal approximation to the binomial distribution? The usual recommendation is that the approximation is good if np
More informationConfidence Intervals for Exponential Reliability
Chapter 408 Confidence Intervals for Exponential Reliability Introduction This routine calculates the number of events needed to obtain a specified width of a confidence interval for the reliability (proportion
More informationISyE 2028 Basic Statistical Methods  Fall 2015 Bonus Project: Big Data Analytics Final Report: Time spent on social media
ISyE 2028 Basic Statistical Methods  Fall 2015 Bonus Project: Big Data Analytics Final Report: Time spent on social media Abstract: The growth of social media is astounding and part of that success was
More informationReview #2. Statistics
Review #2 Statistics Find the mean of the given probability distribution. 1) x P(x) 0 0.19 1 0.37 2 0.16 3 0.26 4 0.02 A) 1.64 B) 1.45 C) 1.55 D) 1.74 2) The number of golf balls ordered by customers of
More informationBA 275 Review Problems  Week 6 (10/30/0611/3/06) CD Lessons: 53, 54, 55, 56 Textbook: pp. 394398, 404408, 410420
BA 275 Review Problems  Week 6 (10/30/0611/3/06) CD Lessons: 53, 54, 55, 56 Textbook: pp. 394398, 404408, 410420 1. Which of the following will increase the value of the power in a statistical test
More information1 SAMPLE SIGN TEST. NonParametric Univariate Tests: 1 Sample Sign Test 1. A nonparametric equivalent of the 1 SAMPLE TTEST.
NonParametric Univariate Tests: 1 Sample Sign Test 1 1 SAMPLE SIGN TEST A nonparametric equivalent of the 1 SAMPLE TTEST. ASSUMPTIONS: Data is nonnormally distributed, even after log transforming.
More informationQuantitative Methods for Finance
Quantitative Methods for Finance Module 1: The Time Value of Money 1 Learning how to interpret interest rates as required rates of return, discount rates, or opportunity costs. 2 Learning how to explain
More informationConfidence Intervals for Cpk
Chapter 297 Confidence Intervals for Cpk Introduction This routine calculates the sample size needed to obtain a specified width of a Cpk confidence interval at a stated confidence level. Cpk is a process
More informationHypothesis testing for µ:
University of California, Los Angeles Department of Statistics Statistics 13 Elements of a hypothesis test: Hypothesis testing Instructor: Nicolas Christou 1. Null hypothesis, H 0 (always =). 2. Alternative
More information14.0 Hypothesis Testing
14.0 Hypothesis Testing 1 Answer Questions Hypothesis Tests Examples 14.1 Hypothesis Tests A hypothesis test (significance test) is a way to decide whether the data strongly support one point of view or
More informationAP STATISTICS (WarmUp Exercises)
AP STATISTICS (WarmUp Exercises) 1. Describe the distribution of ages in a city: 2. Graph a box plot on your calculator for the following test scores: {90, 80, 96, 54, 80, 95, 100, 75, 87, 62, 65, 85,
More informationStat 411/511 THE RANDOMIZATION TEST. Charlotte Wickham. stat511.cwick.co.nz. Oct 16 2015
Stat 411/511 THE RANDOMIZATION TEST Oct 16 2015 Charlotte Wickham stat511.cwick.co.nz Today Review randomization model Conduct randomization test What about CIs? Using a tdistribution as an approximation
More informationExercises  The Normal Curve
Exercises  The Normal Curve 1. Find e following proportions under e Normal curve: a) P(z>2.05) b) P(z>2.5) c) P(1.25
More informationICMSF Lecture on Microbiological Sampling Plans
ICMSF Lecture on Microbiological Sampling Plans Susanne Dahms IAFP, San Diego, 2002 Client  meeting   1 Overview Introduction Sampling plans: Design and means to study their performance Twoclass attributes
More informationMilitary Reliability Modeling William P. Fox, Steven B. Horton
Military Reliability Modeling William P. Fox, Steven B. Horton Introduction You are an infantry rifle platoon leader. Your platoon is occupying a battle position and has been ordered to establish an observation
More information4. Introduction to Statistics
Statistics for Engineers 41 4. Introduction to Statistics Descriptive Statistics Types of data A variate or random variable is a quantity or attribute whose value may vary from one unit of investigation
More informationChapter 1112 1 Review
Chapter 1112 Review Name 1. In formulating hypotheses for a statistical test of significance, the null hypothesis is often a statement of no effect or no difference. the probability of observing the data
More informationLAB 4 INSTRUCTIONS CONFIDENCE INTERVALS AND HYPOTHESIS TESTING
LAB 4 INSTRUCTIONS CONFIDENCE INTERVALS AND HYPOTHESIS TESTING In this lab you will explore the concept of a confidence interval and hypothesis testing through a simulation problem in engineering setting.
More informationSTAT 315: HOW TO CHOOSE A DISTRIBUTION FOR A RANDOM VARIABLE
STAT 315: HOW TO CHOOSE A DISTRIBUTION FOR A RANDOM VARIABLE TROY BUTLER 1. Random variables and distributions We are often presented with descriptions of problems involving some level of uncertainty about
More informationChapter 2: Data quantifiers: sample mean, sample variance, sample standard deviation Quartiles, percentiles, median, interquartile range Dot diagrams
Review for Final Chapter 2: Data quantifiers: sample mean, sample variance, sample standard deviation Quartiles, percentiles, median, interquartile range Dot diagrams Histogram Boxplots Chapter 3: Set
More informationTreatment and analysis of data Applied statistics Lecture 3: Sampling and descriptive statistics
Treatment and analysis of data Applied statistics Lecture 3: Sampling and descriptive statistics Topics covered: Parameters and statistics Sample mean and sample standard deviation Order statistics and
More informationUnderstanding Confidence Intervals and Hypothesis Testing Using Excel Data Table Simulation
Understanding Confidence Intervals and Hypothesis Testing Using Excel Data Table Simulation Leslie Chandrakantha lchandra@jjay.cuny.edu Department of Mathematics & Computer Science John Jay College of
More informationObjectives. Electric Current
Objectives Define electrical current as a rate. Describe what is measured by ammeters and voltmeters. Explain how to connect an ammeter and a voltmeter in an electrical circuit. Explain why electrons travel
More information"Reliability and MTBF Overview"
"Reliability and MTBF Overview" Prepared by Scott Speaks Vicor Reliability Engineering Introduction Reliability is defined as the probability that a device will perform its required function under stated
More informationUnit 1 Practice Problems: Real Estate
Unit 1 Practice Problems: Real Estate PRACTICE PROBLEM 1: Perform a categorical analysis on the construction of the homes. Describe your findings. PRACTICE PROBLEM 2: Create a frequency distribution &
More informationFairfield Public Schools
Mathematics Fairfield Public Schools AP Statistics AP Statistics BOE Approved 04/08/2014 1 AP STATISTICS Critical Areas of Focus AP Statistics is a rigorous course that offers advanced students an opportunity
More informationReliability aspects on Power Supplies
Reliability aspects on Power Supplies Design Note 002 Ericsson Power Modules General Abstract As power supplies are the very heart of every electronic equipment, special attention must be paid to their
More informationAP Statistics 2009 Scoring Guidelines Form B
AP Statistics 2009 Scoring Guidelines Form B The College Board The College Board is a notforprofit membership association whose mission is to connect students to college success and opportunity. Founded
More informationBasic Statistics Self Assessment Test
Basic Statistics Self Assessment Test Professor Douglas H. Jones PAGE 1 A sodadispensing machine fills 12ounce cans of soda using a normal distribution with a mean of 12.1 ounces and a standard deviation
More informationBusiness Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.
Business Course Text Bowerman, Bruce L., Richard T. O'Connell, J. B. Orris, and Dawn C. Porter. Essentials of Business, 2nd edition, McGrawHill/Irwin, 2008, ISBN: 9780073319889. Required Computing
More informationChapter 3 Descriptive Statistics: Numerical Measures. Learning objectives
Chapter 3 Descriptive Statistics: Numerical Measures Slide 1 Learning objectives 1. Single variable Part I (Basic) 1.1. How to calculate and use the measures of location 1.. How to calculate and use the
More informationLecture 10: Other Continuous Distributions and Probability Plots
Lecture 10: Other Continuous Distributions and Probability Plots Devore: Section 4.44.6 Page 1 Gamma Distribution Gamma function is a natural extension of the factorial For any α > 0, Γ(α) = 0 x α 1 e
More informationJoint Probability Distributions and Random Samples. Week 5, 2011 Stat 4570/5570 Material from Devore s book (Ed 8), and Cengage
5 Joint Probability Distributions and Random Samples Week 5, 2011 Stat 4570/5570 Material from Devore s book (Ed 8), and Cengage Two Discrete Random Variables The probability mass function (pmf) of a single
More informationAP Statistics 2001 Solutions and Scoring Guidelines
AP Statistics 2001 Solutions and Scoring Guidelines The materials included in these files are intended for noncommercial use by AP teachers for course and exam preparation; permission for any other use
More informationHomework 5 Solutions
Math 130 Assignment Chapter 18: 6, 10, 38 Chapter 19: 4, 6, 8, 10, 14, 16, 40 Chapter 20: 2, 4, 9 Chapter 18 Homework 5 Solutions 18.6] M&M s. The candy company claims that 10% of the M&M s it produces
More informationJoint Exam 1/P Sample Exam 1
Joint Exam 1/P Sample Exam 1 Take this practice exam under strict exam conditions: Set a timer for 3 hours; Do not stop the timer for restroom breaks; Do not look at your notes. If you believe a question
More informationTransilvania University of Braşov, Romania Study program : Quality Management
Transilvania University of Braşov, Romania Study program : Quality Management Faculty Technological Engineering and Industrial Management Study program (Curriculum) Study period 2 years (master) Academic
More informationEmbedded Systems Lecture 9: Reliability & Fault Tolerance. Björn Franke University of Edinburgh
Embedded Systems Lecture 9: Reliability & Fault Tolerance Björn Franke University of Edinburgh Overview Definitions System Reliability Fault Tolerance Sources and Detection of Errors Stage Error Sources
More informationMath 2015 Lesson 21. We discuss the mean and the median, two important statistics about a distribution. p(x)dx = 0.5
ean and edian We discuss the mean and the median, two important statistics about a distribution. The edian The median is the halfway point of a distribution. It is the point where half the population has
More information2. DATA AND EXERCISES (Geos2911 students please read page 8)
2. DATA AND EXERCISES (Geos2911 students please read page 8) 2.1 Data set The data set available to you is an Excel spreadsheet file called cyclones.xls. The file consists of 3 sheets. Only the third is
More informationApplied Reliability Page 1 APPLIED RELIABILITY. Techniques for Reliability Analysis
Applied Reliability Page 1 APPLIED RELIABILITY Techniques for Reliability Analysis with Applied Reliability Tools (ART) (an EXCEL AddIn) and JMP Software AM216 Class 5 Notes Santa Clara University Copyright
More informationSECOND PART, LECTURE 4: CONFIDENCE INTERVALS
Massimo Guidolin Massimo.Guidolin@unibocconi.it Dept. of Finance STATISTICS/ECONOMETRICS PREP COURSE PROF. MASSIMO GUIDOLIN SECOND PART, LECTURE 4: CONFIDENCE INTERVALS Lecture 4: Confidence Intervals
More informationInvestigating the Investigative Task: Testing for Skewness An Investigation of Different Test Statistics and their Power to Detect Skewness
Investigating the Investigative Task: Testing for Skewness An Investigation of Different Test Statistics and their Power to Detect Skewness Josh Tabor Canyon del Oro High School Journal of Statistics Education
More informationCurriculum Map Statistics and Probability Honors (348) Saugus High School Saugus Public Schools 20092010
Curriculum Map Statistics and Probability Honors (348) Saugus High School Saugus Public Schools 20092010 Week 1 Week 2 14.0 Students organize and describe distributions of data by using a number of different
More informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question
Stats: Test Review Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question Provide an appropriate response. ) Given H0: p 0% and Ha: p < 0%, determine
More informationReview the following from Chapter 5
Bluman, Chapter 6 1 Review the following from Chapter 5 A surgical procedure has an 85% chance of success and a doctor performs the procedure on 10 patients, find the following: a) The probability that
More informationAP * Statistics Review
AP * Statistics Review Confidence Intervals Teacher Packet AP* is a trademark of the College Entrance Examination Board. The College Entrance Examination Board was not involved in the production of this
More informationNonparametric tests, Bootstrapping
Nonparametric tests, Bootstrapping http://www.isrec.isbsib.ch/~darlene/embnet/ Hypothesis testing review 2 competing theories regarding a population parameter: NULL hypothesis H ( straw man ) ALTERNATIVEhypothesis
More informationUnit 26 Estimation with Confidence Intervals
Unit 26 Estimation with Confidence Intervals Objectives: To see how confidence intervals are used to estimate a population proportion, a population mean, a difference in population proportions, or a difference
More informationMATH BOOK OF PROBLEMS SERIES. New from Pearson Custom Publishing!
MATH BOOK OF PROBLEMS SERIES New from Pearson Custom Publishing! The Math Book of Problems Series is a database of math problems for the following courses: Prealgebra Algebra Precalculus Calculus Statistics
More informationStatistical Functions in Excel
Statistical Functions in Excel There are many statistical functions in Excel. Moreover, there are other functions that are not specified as statistical functions that are helpful in some statistical analyses.
More informationInstructions for : TI83, 83Plus, 84Plus for STP classes, Ela Jackiewicz
Computing areas under normal curves: option 2 normalcdf(lower limit, upper limit, mean, standard deviation) will give are between lower and upper limits (mean=0 and St.dev=1 are default values) Ex1 To
More informationFinal Exam Practice Problem Answers
Final Exam Practice Problem Answers The following data set consists of data gathered from 77 popular breakfast cereals. The variables in the data set are as follows: Brand: The brand name of the cereal
More informationExamination 110 Probability and Statistics Examination
Examination 0 Probability and Statistics Examination Sample Examination Questions The Probability and Statistics Examination consists of 5 multiplechoice test questions. The test is a threehour examination
More informationVLSI Design Verification and Testing
VLSI Design Verification and Testing Instructor Chintan Patel (Contact using email: cpatel2@cs.umbc.edu). Text Michael L. Bushnell and Vishwani D. Agrawal, Essentials of Electronic Testing, for Digital,
More informationSTATISTICS FOR PSYCH MATH REVIEW GUIDE
STATISTICS FOR PSYCH MATH REVIEW GUIDE ORDER OF OPERATIONS Although remembering the order of operations as BEDMAS may seem simple, it is definitely worth reviewing in a new context such as statistics formulae.
More informationUnit 18: Accelerated Test Models
Unit 18: Accelerated Test Models Ramón V. León Notes largely based on Statistical Methods for Reliability Data by W.Q. Meeker and L. A. Escobar, Wiley, 1998 and on their class notes. 10/19/2004 Unit 18
More informationCourse Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics
Course Text Business Statistics Lind, Douglas A., Marchal, William A. and Samuel A. Wathen. Basic Statistics for Business and Economics, 7th edition, McGrawHill/Irwin, 2010, ISBN: 9780077384470 [This
More informationIntel Power Management Technologies for Processor Graphics, Display, and Memory White Paper For Desktop and Notebook Platforms August 2010
Intel Power Management Technologies for Processor Graphics, Display, and Memory White Paper For 20102011 Desktop and Notebook Platforms August 2010 Document Number: 324226002 INFORMATION IN THIS DOCUMENT
More informationHardware: Input, Processing, and Output Devices
Hardware: Input, Processing, and Output Devices Computer Systems Hardware Components Execution of an Instruction Processing Characteristics and Functions Physical Characteristics of CPU Memory Characteristics
More informationMath 201: Statistics November 30, 2006
Math 201: Statistics November 30, 2006 Fall 2006 MidTerm #2 Closed book & notes; only an A4size formula sheet and a calculator allowed; 90 mins. No questions accepted! Instructions: There are eleven pages
More informationMT426 Notebook 3 Fall 2012 prepared by Professor Jenny Baglivo. 3 MT426 Notebook 3 3. 3.1 Definitions... 3. 3.2 Joint Discrete Distributions...
MT426 Notebook 3 Fall 2012 prepared by Professor Jenny Baglivo c Copyright 20042012 by Jenny A. Baglivo. All Rights Reserved. Contents 3 MT426 Notebook 3 3 3.1 Definitions............................................
More informationPoint and Interval Estimates
Point and Interval Estimates Suppose we want to estimate a parameter, such as p or µ, based on a finite sample of data. There are two main methods: 1. Point estimate: Summarize the sample by a single number
More informationAgenda. Michele Taliercio, Il circuito Integrato, Novembre 2001
Agenda Introduzione Il mercato Dal circuito integrato al System on a Chip (SoC) La progettazione di un SoC La tecnologia Una fabbrica di circuiti integrati 28 How to handle complexity G The engineering
More informationDensity Curve. A density curve is the graph of a continuous probability distribution. It must satisfy the following properties:
Density Curve A density curve is the graph of a continuous probability distribution. It must satisfy the following properties: 1. The total area under the curve must equal 1. 2. Every point on the curve
More informationContemporary Mathematics Online Math 1030 Sample Exam I Chapters 1214 No Time Limit No Scratch Paper Calculator Allowed: Scientific
Contemporary Mathematics Online Math 1030 Sample Exam I Chapters 1214 No Time Limit No Scratch Paper Calculator Allowed: Scientific Name: The point value of each problem is in the lefthand margin. You
More informationNull Hypothesis Significance Testing Signifcance Level, Power, ttests Spring 2014 Jeremy Orloff and Jonathan Bloom
Null Hypothesis Significance Testing Signifcance Level, Power, ttests 18.05 Spring 2014 Jeremy Orloff and Jonathan Bloom Simple and composite hypotheses Simple hypothesis: the sampling distribution is
More informationAlessandro Birolini. ineerin. Theory and Practice. Fifth edition. With 140 Figures, 60 Tables, 120 Examples, and 50 Problems.
Alessandro Birolini Re ia i it En ineerin Theory and Practice Fifth edition With 140 Figures, 60 Tables, 120 Examples, and 50 Problems ~ Springer Contents 1 Basic Concepts, Quality and Reliability Assurance
More informationPractice problems for Homework 12  confidence intervals and hypothesis testing. Open the Homework Assignment 12 and solve the problems.
Practice problems for Homework 1  confidence intervals and hypothesis testing. Read sections 10..3 and 10.3 of the text. Solve the practice problems below. Open the Homework Assignment 1 and solve the
More informationThe Big 50 Revision Guidelines for S1
The Big 50 Revision Guidelines for S1 If you can understand all of these you ll do very well 1. Know what is meant by a statistical model and the Modelling cycle of continuous refinement 2. Understand
More informationApplication Note. Line Card Redundancy Design With the XRT83SL38 T1/E1 SH/LH LIU ICs
Application Note Design With the XRT83SL38 T1/E1 SH/LH LIU ICs Revision 1.3 1 REDUNDANCY APPLICATIONS INTRODUCTION Telecommunication system design requires signal integrity and reliability. When a T1/E1
More informationCHAPTER 1 THE CERTIFIED QUALITY ENGINEER EXAM. 1.0 The Exam. 2.0 Suggestions for Study. 3.0 CQE Examination Content. Where shall I begin your majesty?
QReview 1 CHAPTER 1 THE CERTIFIED QUALITY ENGINEER EXAM 1.0 The Exam 2.0 Suggestions for Study 3.0 CQE Examination Content Where shall I begin your majesty? The White Rabbit Begin at the beginning, and
More informationSHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.
Math 1342 (Elementary Statistics) Test 2 Review SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. Find the indicated probability. 1) If you flip a coin
More informationExperimental Design. Power and Sample Size Determination. Proportions. Proportions. Confidence Interval for p. The Binomial Test
Experimental Design Power and Sample Size Determination Bret Hanlon and Bret Larget Department of Statistics University of Wisconsin Madison November 3 8, 2011 To this point in the semester, we have largely
More informationThe Health Benefits of Stress
Snapshots of Doctoral Research at University College Cork 2014 Rosemary O Keeffe Electrical and Electronic Engineering, School of Engineering, UCC Stressed Out Everyone knows that stress is bad for your
More information