Chapter Eleven Quality and Assurance. Chapter Eleven Quality and Assurance.

Slides:



Advertisements
Similar presentations
A.P. STATISTICS LESSON 7 – 1 ( DAY 1 ) DISCRETE AND CONTINUOUS RANDOM VARIABLES.
Advertisements

Chapter 6 The Normal Distribution In this handout: Probability model for a continuous random variable Normal distribution.
3.3 Toward Statistical Inference. What is statistical inference? Statistical inference is using a fact about a sample to estimate the truth about the.
MA 102 Statistical Controversies Monday, April 1, 2002 Today: Randomness and probability Probability models and rules Reading (for Wednesday): Chapter.
Continuous Random Variables and Probability Distributions
Copyright © 2008 Pearson Education, Inc. Chapter 11 Probability and Calculus Copyright © 2008 Pearson Education, Inc.
CS 351/ IT 351 Modelling and Simulation Technologies Random Variates Dr. Jim Holten.
Probability and Sampling Theory and the Financial Bootstrap Tools (Part 2) IEF 217a: Lecture 2.b Fall 2002 Jorion chapter 4.
Continuous Random Variables Chap. 12. COMP 5340/6340 Continuous Random Variables2 Preamble Continuous probability distribution are not related to specific.
CHAPTER 6 Statistical Analysis of Experimental Data
2003/04/24 Chapter 5 1頁1頁 Chapter 5 : Sums of Random Variables & Long-Term Averages 5.1 Sums of Random Variables.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 6-1 Chapter 6 The Normal Distribution and Other Continuous Distributions.
Introduction to Normal Distributions and the Standard Distribution
Statistical Process Control
L7.1b Continuous Random Variables CONTINUOUS RANDOM VARIABLES NORMAL DISTRIBUTIONS AD PROBABILITY DISTRIBUTIONS.
1 Chapter Seven Introduction to Sampling Distributions Section 1 Sampling Distribution.
Chapter 14 Monte Carlo Simulation Introduction Find several parameters Parameter follow the specific probability distribution Generate parameter.
Slide Copyright © 2008 Pearson Education, Inc. Chapter 7 The Sampling Distribution of the Sample Mean.
Introduction to Summary Statistics
SAMPLING DISTRIBUTIONS Let’s do a little review :.
The Normal Distribution Chapter 6. Outline 6-1Introduction 6-2Properties of a Normal Distribution 6-3The Standard Normal Distribution 6-4Applications.
CHAPTER 11 Quality and Assurance McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.
Copyright © 2010 Pearson Addison-Wesley. All rights reserved. Chapter 6 Some Continuous Probability Distributions.
Chapter 7 Sampling and Sampling Distributions ©. Simple Random Sample simple random sample Suppose that we want to select a sample of n objects from a.
Chapter 7: Introduction to Sampling Distributions Section 2: The Central Limit Theorem.
Simulation Example: Generate a distribution for the random variate: What is the approximate probability that you will draw X ≤ 1.5?
Random Sampling Approximations of E(X), p.m.f, and p.d.f.
 How do you know how long your design is going to last?  Is there any way we can predict how long it will work?  Why do Reliability Engineers get paid.
© 2010 Pearson Prentice Hall. All rights reserved Chapter The Normal Probability Distribution © 2010 Pearson Prentice Hall. All rights reserved 3 7.
Statistics. A two-dimensional random variable with a uniform distribution.
INTRODUCTORY MATHEMATICAL ANALYSIS For Business, Economics, and the Life and Social Sciences  2011 Pearson Education, Inc. Chapter 16 Continuous Random.
Copyright © 2013 Pearson Education, Inc. All rights reserved Chapter 5 Continuous Random Variables.
Copyright © 2013, 2010 and 2007 Pearson Education, Inc. Chapter The Normal Probability Distribution 7.
The Normal Distribution
The Sampling Distribution of the Sample Mean
Chapter 20 Statistical Considerations Lecture Slides The McGraw-Hill Companies © 2012.
 I can identify the shape of a data distribution using statistics or charts.  I can make inferences about the population from the shape of a sample.
Chapter 7 The Normal Probability Distribution 7.1 Properties of the Normal Distribution.
Chapter 5 Joint Probability Distributions and Random Samples  Jointly Distributed Random Variables.2 - Expected Values, Covariance, and Correlation.3.
AP Stats Chapter 7 Review Nick Friedl, Patrick Donovan, Jay Dirienzo.
Win – W Loss – L 7W7W 11 W 2L2L 3L3L 12 L 7 not on 1 st roll - L 1 st sum Repea ted W
Sampling and Sampling Distributions
Chapter 7 The Normal Probability Distribution
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Random Variable 2013.
Continuous Random Variables
Chapter 4 Continuous Random Variables and Probability Distributions
Random Variables and Probability Distribution (2)
Basic Business Statistics (8th Edition)
STAT 311 REVIEW (Quick & Dirty)
Continuous Random Variables
IENG 486: Statistical Quality & Process Control
Econ Roadmap Focus Midterm 1 Focus Midterm 2 Focus Final Intro
AP Statistics: Chapter 7
Chapter 3.
Continuous Random Variables
Suppose you roll two dice, and let X be sum of the dice. Then X is
The Normal Probability Distribution Summary
IENG 486: Statistical Quality & Process Control
Lecture Slides Elementary Statistics Twelfth Edition
Lecture Slides Elementary Statistics Twelfth Edition
Chapter 6 Some Continuous Probability Distributions.
ASV Chapters 1 - Sample Spaces and Probabilities
Chapter 14 Monte Carlo Simulation
Vital Statistics Probability and Statistics for Economics and Business
Probability Distribution.
Chapter 3 : Random Variables
Probability Distribution.
Chapter 7 The Normal Distribution and Its Applications
Accuracy of Averages.
Presentation transcript:

Chapter Eleven Quality and Assurance

The Trade-Off Between Quality and Cost Fig. 11-1 The Trade-Off Between Quality and Cost

Probability Density of a Uniform Variate on (0, 1) Fig. 11-2 Probability Density of a Uniform Variate on (0, 1)

Density of the Sum of Three Uniform Random Variables Fig. 11-3 Density of the Sum of Three Uniform Random Variables

Fig. 11-4 Density of the Sum of Three Uniform Random Variables and the Normal Approximation

Frequency Histogram of 150 Measurements Fig. 11-5 Frequency Histogram of 150 Measurements

Theoretical Normal Curve of Arm Length Fig. 11-6 Theoretical Normal Curve of Arm Length

Chart for Tracking Arm Data Fig. 11-7 Chart for Tracking Arm Data

R Chart for Tracking Arm Data Fig. 11-8 R Chart for Tracking Arm Data

Preliminary p chart for Xezet floppy disk data (Refer to Example 11.2) Fig. 11-9 Preliminary p chart for Xezet floppy disk data (Refer to Example 11.2)

Revised p chart for Xezet floppy disk data (Refer to Example 11.2) Fig. 11-10 Revised p chart for Xezet floppy disk data (Refer to Example 11.2)

Successive Cycles in Process Monitoring Fig. 11-11 Successive Cycles in Process Monitoring

The Behavior of G(n, k) as a function of k (Refer to Example 11.5) Fig. 11-12 The Behavior of G(n, k) as a function of k (Refer to Example 11.5)

Fig. 11-13 The Ideal OC Curve

OC Curve for Spire Records (n = 10) Fig. 11-14 OC Curve for Spire Records (n = 10)

Revised OC Curve for Spire Records (n = 25) Fig. 11-15 Revised OC Curve for Spire Records (n = 25)

Two Realizations of a Sequential Sampling Plan Fig. 11-16 Two Realizations of a Sequential Sampling Plan

Sequential Sampling Plan for Spire Records (Refer to Example 11.8) Fig. 11-17 Sequential Sampling Plan for Spire Records (Refer to Example 11.8)

ASN Curve for Spire Records (estimated) Fig. 11-18 ASN Curve for Spire Records (estimated)

AOQ Curves for Spire Records (Refer to Example 11.9) Fig. 11-19 AOQ Curves for Spire Records (Refer to Example 11.9)

The House of Quality: The QFD Planning Matrix Fig. 11-20 The House of Quality: The QFD Planning Matrix