LEAN Six Sigma Green Belt
|
|
- Kelley Cannon
- 5 years ago
- Views:
Transcription
1 LEAN Six Sigma Green Belt First Edition Manual Featuring SigmaXL Statistical Software v.7 A LSV Group A/S Publication LSV Group A/S LSV Group is accredited and certified by the IASSC. IASSC is a professional Association dedicated to growing and enhancing the standards within the LEAN Six Sigma Community LSV Group A/S LEAN Six Sigma Green Belt Manual Copyright, 2015 LSV Group A/S. All rights reserved. Individual Copy. No portion of these materials may be reproduced, transmitted, stored in a retrieval or translated into any language in any form or by any means without the prior written permission from LSV Group A/S
2 Introduction Define Phase Six Sigma Overview What is Six Sigma? Six Sigma History Six Sigma Approach Six Sigma Methodology Roles and Responsibilities Six Sigma Fundamentals Defining a Process Quality Function Deployment Cost of Poor Quality Pareto Charts and Analysis Six Sigma Projects Six Sigma Metrics Business Case and Charter Project Team Selection Project Risk Management Project Planning Lean Fundamentals Lean and Six Sigma History of Lean Seven Deadly Muda Five-S (5S) Measure Phase Process Definition Cause and Effect Diagram Cause and Effects Matrix Failure Modes and Effects Analysis (FMEA) Theory of Constraints Six Sigma Statistics LSV Group A/S 1
3 2.2.1 Basic Statistics Descriptive Statistics Normal Distribution and Normality Graphical Analysis Measurement System Analysis Precision and Accuracy Bias, Linearity, and Stability Gage Repeatability and Reproducibility Variable and Attribute MSA Process Capability Capability Analysis Concept of Stability Attribute and Discrete Capability Monitoring Techniques Analyze Phase Inferential Statistics Understanding Inference Sampling Techniques Sample Size Central Limit Theorem Hypothesis Testing Goals of Hypothesis Testing Statistical Significance Risk; Alpha and Beta Types of Hypothesis Tests Hypothesis Tests: Normal Data One and Two Sample T-Tests One Sample Variance One-Way ANOVA Hypothesis Testing Non-Normal Data Mann Whitney LSV Group A/S 2
4 3.4.2 Kruskal Wallis Mood s Median Friedman One Sample Sign One Sample Wilcoxon One and Two Sample Proportion Chi-Squared (Contingency Tables) Tests of Equal Variance Improve Phase Simple Linear Regression Correlation X-Y Diagram Regression Equations Residuals Analysis Multiple Regression Analysis Non-Linear Regression Multiple Linear Regression Confidence and Prediction Intervals Residuals Analysis Control Phase Lean Controls Control Methods for 5S Kanban Poka-Yoke Statistical Process Control Data Collection for SPC I-MR Chart Xbar-R Chart U Chart P Chart NP Chart LSV Group A/S 3
5 5.2.7 X-S Chart CumSum Chart EWMA Chart Control Methods Control Chart Anatomy Subgroups and Sampling Six Sigma Control Plans Cost Benefit Analysis Elements of Control Plans Response Plan Elements Index LSV Group A/S 4
6 I NTRODUCTION LEAN Six Sigma has become our generation s most outspoken process optimization concept, and used right and to their fullest, it can turnaround or empower a business beyond imagination. Being a world class provider in today s market field depends on your ability to meet your customers expectations and demands. Most people know that the customer has the power to make your company either a success or a failure. You need to be better than your competitors and create a trustworthy relationship with your customer in order to be successful. LEAN Six Sigma is a methodology based on gaining customer satisfaction by reducing defects in the process. LEAN Six Sigma is all about becoming faster better and cheaper than your competitor. LEAN Six Sigma is a powerful toolkit for maximizing productivity, profitability and growth. With this LEAN Six Sigma education you will learn how to listen to your customers and meet their expectations. You will be able to conduct your process around the expectations of customers. Furthermore, you will learn how to lower cost and eliminate waste from your processes and reduce variation and defects, which have a negative impact on your customers. We believe that this book contains all of the aspects needed to become a great LEAN Six Sigma practitioner. We are sure that this book will help you become a successful Green Belt. During this course you will learn the terminology within LEAN Six Sigma and be able to structurally work with process improvement projects on your own. This course is giving you the ability to have a leading role in future improvement projects. How to use this book? This book has been written to explain the topics of Lean Six Sigma and provide step by step instructions on how to perform key statistical analysis techniques using SigmaXL. As expected from an international provider of LEAN Six Sigma educations, this book is built around the DMAIC approach, and is a step by step roadmap to improving existing processes. During the course we will use this book as our main guideline. Every step in this book will be needed during your first process improving project (your learning project), and you will have to understand and apply every single step before moving on to the next step in the DMAIC approach. After you have finished this course, the book will serve as a reference guide every time you are working with process optimization or just need to read up on a specific tool. Always remember to go through the steps of DMAIC chronologically when working with an optimization project. LSV Group A/S 5
7 1.1 SIX SIGMA OVERVIEW WHAT IS SIX SIGMA? In statistics, sigma (σ) refers to standard deviation, which is a measure of variation. You will come to learn that variation is the enemy of any quality process; it makes it much more difficult to meet a customer s expectation for a product or service. We need to understand, manage, and minimize process variation. Six Sigma is an aspiration or goal of process performance. A Six Sigma goal is for a process average to operate approximately 6σ away from customer s high and low specification limits. A process whose average is about 6σ away from the customer s high and low specification limits has abundant room to float before approaching the customer s specification limits. Most people think of Six Sigma as a disciplined, data-driven approach to eliminating defects and solving business problems. If you break down the term, Six Sigma, the two words describe a measure of quality that strives for near perfection. A Six Sigma process only yields 3.4 defects for every 1 million opportunities! In other words, % of the products are defect-free, but some processes require more quality and some require less. Fig. 1.1 Six Sigma Process with mean 6 standard deviations away from either specification limit. The more variation that can be reduced in the process (by narrowing the distribution), the more easily the customer s expectations can be met. LSV Group A/S 11
8 Figure 1.28 depicts a full House of Quality with each room labeled. In summary the rooms are: Customer Requirements Technical Specifications Relationship Matrix Prioritized Customer Requirements Competitive Assessment Correlation Matrix Prioritized Design Requirements Fig House of Quality Pros of QFD Focuses the design of the product or process on satisfying customer s needs and wants. Improves the contact channels between customers, advertising, research and improvement, quality and production departments, which sustains better decision making. Reduces the new product development project period and cost. LSV Group A/S 51
9 1.4 LEAN FUNDAMENTALS LEAN AND SIX SIGMA What is Lean? A Lean enterprise is one which intends to eliminate waste and allow only value to be pulled through its system. A Lean enterprise can be achieved by identifying and effectively eliminating all waste (which will result in a flowing, cost-effective system). A Lean manufacturing system drives value, flows smoothly, maximizes production, and minimizes waste. Lean manufacturing is characterized by: Identifying and driving value Establishing flow and pull systems Creating production availability and flexibility Zero waste Waste elimination Waste identification and elimination is critical to any successful Lean enterprise Elimination of waste enables flow, drives value, cuts cost, and provides flexible and available production The Five Lean Principles The following five principles of Lean are taken from the book Lean Thinking (1996) by James P. Womack and Daniel T. Jones. 1. Specify value desired by customers. 2. Identify the value stream. 3. Make the product flow continuous. 4. Introduce pull systems where continuous flow is possible. 5. Manage toward perfection so that the number of steps and the amount of time and information needed to serve the customer continually falls. Principle 1: Specify Value Defined by Customers Only a small fraction of the total time and effort spent in an organization actually adds value for the end customer. With a clear definition of value (from the customer s perspective), it is much easier to identify where the waste is. Principle 2: Identify the Value Stream The value stream is the entire set of activities across all parts of the organization involved in jointly delivering the product or service. It is the end-to-end process that delivers the value to the customer. As stated above, once you understand what determines value to the customer, it is easier to determine where the waste is. LSV Group A/S 85
10 3.1 INFERENTIAL STATISTICS UNDERSTANDING INFERENCE What is Statistical Inference? Statistical inference is the process of making inferences regarding the characteristics of an unobservable population based on the characteristics of an observed sample. Statistical inference is widely used since it is difficult or sometimes impossible to collect the entire population data. It is rare that we ever know the characteristics of a population, so we need to take limited data and infer what the population looks like. Outcome of Statistical Inference The outcome or conclusion of statistical inference is a statistical proposition about the population, such as an estimate of the population mean or standard deviation. Examples of statistical propositions: Estimating a population parameter Identifying an interval or a region where the true population parameter would fall with some certainty Deciding whether to reject a hypothesis made on characteristics of the population of interest Making predictions Clustering or partitioning data into different groups Population and Sample A statistical population is an entire set of objects or observations about which statistical inferences are to be drawn based on its sample. It is usually impractical or impossible to obtain the data for the entire population. For example, if we are interested in analyzing the population of all the trees, it is extremely difficult to collect the data for all the trees that existed in the past, exist now, and will exist in the future. A sample is a subset of the population (like a piece of the pie above). It is necessary for samples to be representative of the population. The process of selecting a subset of observations within a population is referred to as sampling. Fig 3.1 Sampling a statistical population LSV Group A/S 161
11 Hypothesis Testing Conclusion There are two possible conclusions of hypothesis testing: 1. Reject the null 2. Fail to reject the null When there is enough evidence based on the sample information to prove the alternative hypothesis, we reject the null. When there is not enough evidence or the sample information is not sufficiently persuasive, we fail to reject the null. Decision Rules in Hypothesis Testing Fig 3.14 Rules in Hypothesis Testing As we get into the technicalities of hypothesis testing, it is important to understand some terms as they pertain to a distribution. Consider in this picture a normal distribution, and what we know about the distribution. Remember ? The amount of data that falls within +/ 1, 2, and 3 standard deviations of the mean. The test statistic in hypothesis testing is a value calculated using a function of the sample. Test statistics are considered the sample data s numerical summary that can be used in hypothesis testing. Different hypothesis tests have different formulas to calculate the test statistic. The critical value in hypothesis testing is a threshold value to which the test statistic is compared in order to determine whether the null hypothesis is rejected. The critical value is obtained from statistical tables. Different hypothesis tests need different statistical tables for critical values. Hypothesis testing is made easy with our fancy software packages, but it is important that you understand how the theory and rules work behind the software. LSV Group A/S 179
12 I-MR Charts Diagnosis Fig 5.8 I-MR Charts Diagnosis I Chart (Individuals Chart): Since the MR chart is out of control, the I chart is invalid. MR Chart (Moving Range Chart): Two data points fall beyond the upper control limit. This indicates the MR chart is out of control (i.e., the variations between every two contiguous individual samples are not stable over time). We need to further investigate the process, identify the root causes that trigger the outliers, and correct them to bring the process back in control XBAR-R CHART Xbar-R Chart The Xbar-R chart is a control chart for continuous data with a constant subgroup size between two and ten. The Xbar chart plots the average of a subgroup as a data point. The R chart plots the difference between the highest and lowest values within a subgroup as a data point. The Xbar chart monitors the process mean and the R chart monitors the variation within subgroups. The Xbar is valid only if the R chart is in control. The underlying distribution of the Xbar-R chart is normal distribution. Xbar Chart Equations Xbar chart LSV Group A/S 314
13 Test 2: Nine points in a row on the same side of the center line. Fig 5.44 Western Electric Test 2 Test 2 identifies situations where the process mean has temporarily shifts in the process. Test 3: Six points in a row steadily increasing or steadily decreasing. Test 3 identifies significant trends in performance. Fig 5.45 Western Electric Test 3 Test 4: Fourteen points in a row alternating up and down. Test 4 indicates a cycle. Fig 5.45 Western Electric Test 4 LSV Group A/S 337
APPENDIX A: Process Sigma Table (I)
APPENDIX A: Process Sigma Table (I) 305 APPENDIX A: Process Sigma Table (II) 306 APPENDIX B: Kinds of variables This summary could be useful for the correct selection of indicators during the implementation
More informationVisit us at:
White Paper Integrating Six Sigma and Software Testing Process for Removal of Wastage & Optimizing Resource Utilization 24 October 2013 With resources working for extended hours and in a pressurized environment,
More informationCertified Six Sigma Professionals International Certification Courses in Six Sigma Green Belt
Certification Singapore Institute Certified Six Sigma Professionals Certification Courses in Six Sigma Green Belt ly Licensed Course for Process Improvement/ Assurance Managers and Engineers Leading the
More informationProbability and Statistics Curriculum Pacing Guide
Unit 1 Terms PS.SPMJ.3 PS.SPMJ.5 Plan and conduct a survey to answer a statistical question. Recognize how the plan addresses sampling technique, randomization, measurement of experimental error and methods
More informationGreen Belt Curriculum (This workshop can also be conducted on-site, subject to price change and number of participants)
Green Belt Curriculum (This workshop can also be conducted on-site, subject to price change and number of participants) Notes: 1. We use Mini-Tab in this workshop. Mini-tab is available for free trail
More information2 Lean Six Sigma Green Belt Skill Set
2 Lean Six Sigma Green Belt Skill Set 3 LEAN SIX SIGMA GREEN BELT SKILL SET A GUIDELINE FOR LEAN SIX SIGMA GREEN BELT TRAINING AND CERTIFICATION H.C. Theisens; A. Meek; D. Harborne VERSION 2.4 Lean Six
More informationCertified Six Sigma - Black Belt VS-1104
Certified Six Sigma - Black Belt VS-1104 Certified Six Sigma - Black Belt Professional Certified Six Sigma - Black Belt Professional Certification Code VS-1104 Vskills certification for Six Sigma - Black
More informationSTA 225: Introductory Statistics (CT)
Marshall University College of Science Mathematics Department STA 225: Introductory Statistics (CT) Course catalog description A critical thinking course in applied statistical reasoning covering basic
More informationReduce the Failure Rate of the Screwing Process with Six Sigma Approach
Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management Bali, Indonesia, January 7 9, 2014 Reduce the Failure Rate of the Screwing Process with Six Sigma Approach
More informationProblem Solving for Success Handbook. Solve the Problem Sustain the Solution Celebrate Success
Problem Solving for Success Handbook Solve the Problem Sustain the Solution Celebrate Success Problem Solving for Success Handbook Solve the Problem Sustain the Solution Celebrate Success Rod Baxter 2015
More informationIntroduction on Lean, six sigma and Lean game. Remco Paulussen, Statistics Netherlands Anne S. Trolie, Statistics Norway
Introduction on Lean, six sigma and Lean game Remco Paulussen, Statistics Netherlands Anne S. Trolie, Statistics Norway 1 Lean is. a philosophy a method a set of tools Waste reduction User value Create
More informationAlgebra 1, Quarter 3, Unit 3.1. Line of Best Fit. Overview
Algebra 1, Quarter 3, Unit 3.1 Line of Best Fit Overview Number of instructional days 6 (1 day assessment) (1 day = 45 minutes) Content to be learned Analyze scatter plots and construct the line of best
More informationModule Title: Managing and Leading Change. Lesson 4 THE SIX SIGMA
Module Title: Managing and Leading Change Lesson 4 THE SIX SIGMA Learning Objectives: At the end of the lesson, the students should be able to: 1. Define what is Six Sigma 2. Discuss the brief history
More informationThe Lean And Six Sigma Sinergy
International Journal for Quality research UDK- 658.5 / 006.83 Short Scientific Paper (1.03) The Lean And Six Sigma Sinergy Mirko Sokovic 1) D. Pavletic 2) 1) University of Ljubljana, 2) University of
More informationAGS THE GREAT REVIEW GAME FOR PRE-ALGEBRA (CD) CORRELATED TO CALIFORNIA CONTENT STANDARDS
AGS THE GREAT REVIEW GAME FOR PRE-ALGEBRA (CD) CORRELATED TO CALIFORNIA CONTENT STANDARDS 1 CALIFORNIA CONTENT STANDARDS: Chapter 1 ALGEBRA AND WHOLE NUMBERS Algebra and Functions 1.4 Students use algebraic
More informationInstructor: Mario D. Garrett, Ph.D. Phone: Office: Hepner Hall (HH) 100
San Diego State University School of Social Work 610 COMPUTER APPLICATIONS FOR SOCIAL WORK PRACTICE Statistical Package for the Social Sciences Office: Hepner Hall (HH) 100 Instructor: Mario D. Garrett,
More informationSoftware Maintenance
1 What is Software Maintenance? Software Maintenance is a very broad activity that includes error corrections, enhancements of capabilities, deletion of obsolete capabilities, and optimization. 2 Categories
More informationScienceDirect. A Lean Six Sigma (LSS) project management improvement model. Alexandra Tenera a,b *, Luis Carneiro Pintoª. 27 th IPMA World Congress
Available online at www.sciencedirect.com ScienceDirect Procedia - Social and Behavioral Scien ce s 119 ( 2014 ) 912 920 27 th IPMA World Congress A Lean Six Sigma (LSS) project management improvement
More informationLean Six Sigma Innovative Safety Management
Session No. 561 Introduction Lean Six Sigma Innovative Safety Management Peter G. Furst, MBA, RA, CSP, ARM, REA Liberty Mutual Group Pleasanton, California The organization s safety effort is to create
More informationEdexcel GCSE. Statistics 1389 Paper 1H. June Mark Scheme. Statistics Edexcel GCSE
Edexcel GCSE Statistics 1389 Paper 1H June 2007 Mark Scheme Edexcel GCSE Statistics 1389 NOTES ON MARKING PRINCIPLES 1 Types of mark M marks: method marks A marks: accuracy marks B marks: unconditional
More informationAn Introduction to Simio for Beginners
An Introduction to Simio for Beginners C. Dennis Pegden, Ph.D. This white paper is intended to introduce Simio to a user new to simulation. It is intended for the manufacturing engineer, hospital quality
More informationNCEO Technical Report 27
Home About Publications Special Topics Presentations State Policies Accommodations Bibliography Teleconferences Tools Related Sites Interpreting Trends in the Performance of Special Education Students
More informationChapters 1-5 Cumulative Assessment AP Statistics November 2008 Gillespie, Block 4
Chapters 1-5 Cumulative Assessment AP Statistics Name: November 2008 Gillespie, Block 4 Part I: Multiple Choice This portion of the test will determine 60% of your overall test grade. Each question is
More informationResearch Design & Analysis Made Easy! Brainstorming Worksheet
Brainstorming Worksheet 1) Choose a Topic a) What are you passionate about? b) What are your library s strengths? c) What are your library s weaknesses? d) What is a hot topic in the field right now that
More informationMeasurement & Analysis in the Real World
Measurement & Analysis in the Real World Tools for Cleaning Messy Data Will Hayes SEI Robert Stoddard SEI Rhonda Brown SEI Software Solutions Conference 2015 November 16 18, 2015 Copyright 2015 Carnegie
More informationSTABILISATION AND PROCESS IMPROVEMENT IN NAB
STABILISATION AND PROCESS IMPROVEMENT IN NAB Authors: Nicole Warren Quality & Process Change Manager, Bachelor of Engineering (Hons) and Science Peter Atanasovski - Quality & Process Change Manager, Bachelor
More informationThe Lean Six Sigma Green Belt Examination. Rationale
The Lean Six Sigma Green elt Examination Rationale isqi GmbH 2016 1 U60323 - Level III reating Stable and Efficient Processes escribe and review qualitative and quantitative data, continuous (variables)
More informationState University of New York at Buffalo INTRODUCTION TO STATISTICS PSC 408 Fall 2015 M,W,F 1-1:50 NSC 210
1 State University of New York at Buffalo INTRODUCTION TO STATISTICS PSC 408 Fall 2015 M,W,F 1-1:50 NSC 210 Dr. Michelle Benson mbenson2@buffalo.edu Office: 513 Park Hall Office Hours: Mon & Fri 10:30-12:30
More informationFor Portfolio, Programme, Project, Risk and Service Management. Integrating Six Sigma and PRINCE Mike Ward, Outperfom
For Portfolio, Programme, Project, Risk and Service Management Integrating Six Sigma and PRINCE2 2009 Mike Ward, Outperfom White Paper July 2009 2 Integrating Six Sigma and PRINCE2 2009 Abstract A number
More information12- A whirlwind tour of statistics
CyLab HT 05-436 / 05-836 / 08-534 / 08-734 / 19-534 / 19-734 Usable Privacy and Security TP :// C DU February 22, 2016 y & Secu rivac rity P le ratory bo La Lujo Bauer, Nicolas Christin, and Abby Marsh
More informationLearning From the Past with Experiment Databases
Learning From the Past with Experiment Databases Joaquin Vanschoren 1, Bernhard Pfahringer 2, and Geoff Holmes 2 1 Computer Science Dept., K.U.Leuven, Leuven, Belgium 2 Computer Science Dept., University
More informationStatewide Framework Document for:
Statewide Framework Document for: 270301 Standards may be added to this document prior to submission, but may not be removed from the framework to meet state credit equivalency requirements. Performance
More informationLecture 1: Machine Learning Basics
1/69 Lecture 1: Machine Learning Basics Ali Harakeh University of Waterloo WAVE Lab ali.harakeh@uwaterloo.ca May 1, 2017 2/69 Overview 1 Learning Algorithms 2 Capacity, Overfitting, and Underfitting 3
More informationFunctional Skills Mathematics Level 2 assessment
Functional Skills Mathematics Level 2 assessment www.cityandguilds.com September 2015 Version 1.0 Marking scheme ONLINE V2 Level 2 Sample Paper 4 Mark Represent Analyse Interpret Open Fixed S1Q1 3 3 0
More informationOffice Hours: Mon & Fri 10:00-12:00. Course Description
1 State University of New York at Buffalo INTRODUCTION TO STATISTICS PSC 408 4 credits (3 credits lecture, 1 credit lab) Fall 2016 M/W/F 1:00-1:50 O Brian 112 Lecture Dr. Michelle Benson mbenson2@buffalo.edu
More informationThe Application of Lean Six Sigma in Alleviating Water Shortage in Limpopo Rural Area to Avoid Societal Disaster
The Application of Lean Six Sigma in Alleviating Water Shortage in Limpopo Rural Area to Avoid Societal Disaster S. Ngoune, P. Kholopane Department of Quality and Operations Management, University of Johannesburg,
More informationVOL. 3, NO. 5, May 2012 ISSN Journal of Emerging Trends in Computing and Information Sciences CIS Journal. All rights reserved.
Exploratory Study on Factors that Impact / Influence Success and failure of Students in the Foundation Computer Studies Course at the National University of Samoa 1 2 Elisapeta Mauai, Edna Temese 1 Computing
More informationValue Creation Through! Integration Workshop! Value Stream Analysis and Mapping for PD! January 31, 2002!
Presented by:! Hugh McManus for Rich Millard! MIT! Value Creation Through! Integration Workshop! Value Stream Analysis and Mapping for PD!!!! January 31, 2002! Steps in Lean Thinking (Womack and Jones)!
More informationThe lab is designed to remind you how to work with scientific data (including dealing with uncertainty) and to review experimental design.
Name: Partner(s): Lab #1 The Scientific Method Due 6/25 Objective The lab is designed to remind you how to work with scientific data (including dealing with uncertainty) and to review experimental design.
More informationPython Machine Learning
Python Machine Learning Unlock deeper insights into machine learning with this vital guide to cuttingedge predictive analytics Sebastian Raschka [ PUBLISHING 1 open source I community experience distilled
More informationUNIT ONE Tools of Algebra
UNIT ONE Tools of Algebra Subject: Algebra 1 Grade: 9 th 10 th Standards and Benchmarks: 1 a, b,e; 3 a, b; 4 a, b; Overview My Lessons are following the first unit from Prentice Hall Algebra 1 1. Students
More informationCHAPTER 4: REIMBURSEMENT STRATEGIES 24
CHAPTER 4: REIMBURSEMENT STRATEGIES 24 INTRODUCTION Once state level policymakers have decided to implement and pay for CSR, one issue they face is simply how to calculate the reimbursements to districts
More informationCal s Dinner Card Deals
Cal s Dinner Card Deals Overview: In this lesson students compare three linear functions in the context of Dinner Card Deals. Students are required to interpret a graph for each Dinner Card Deal to help
More informationUniversity of Groningen. Systemen, planning, netwerken Bosman, Aart
University of Groningen Systemen, planning, netwerken Bosman, Aart IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document
More informationFocus on. Learning THE ACCREDITATION MANUAL 2013 WASC EDITION
Focus on Learning THE ACCREDITATION MANUAL ACCREDITING COMMISSION FOR SCHOOLS, WESTERN ASSOCIATION OF SCHOOLS AND COLLEGES www.acswasc.org 10/10/12 2013 WASC EDITION Focus on Learning THE ACCREDITATION
More informationModule 12. Machine Learning. Version 2 CSE IIT, Kharagpur
Module 12 Machine Learning 12.1 Instructional Objective The students should understand the concept of learning systems Students should learn about different aspects of a learning system Students should
More informationMath-U-See Correlation with the Common Core State Standards for Mathematical Content for Third Grade
Math-U-See Correlation with the Common Core State Standards for Mathematical Content for Third Grade The third grade standards primarily address multiplication and division, which are covered in Math-U-See
More informationGDP Falls as MBA Rises?
Applied Mathematics, 2013, 4, 1455-1459 http://dx.doi.org/10.4236/am.2013.410196 Published Online October 2013 (http://www.scirp.org/journal/am) GDP Falls as MBA Rises? T. N. Cummins EconomicGPS, Aurora,
More informationStatistical Analysis of Climate Change, Renewable Energies, and Sustainability An Independent Investigation for Introduction to Statistics
5/22/2012 Statistical Analysis of Climate Change, Renewable Energies, and Sustainability An Independent Investigation for Introduction to Statistics College of Menominee Nation & University of Wisconsin
More informationGrade 6: Correlated to AGS Basic Math Skills
Grade 6: Correlated to AGS Basic Math Skills Grade 6: Standard 1 Number Sense Students compare and order positive and negative integers, decimals, fractions, and mixed numbers. They find multiples and
More informationOn-Line Data Analytics
International Journal of Computer Applications in Engineering Sciences [VOL I, ISSUE III, SEPTEMBER 2011] [ISSN: 2231-4946] On-Line Data Analytics Yugandhar Vemulapalli #, Devarapalli Raghu *, Raja Jacob
More informationMinitab Tutorial (Version 17+)
Minitab Tutorial (Version 17+) Basic Commands and Data Entry Graphical Tools Descriptive Statistics Outline Minitab Basics Basic Commands, Data Entry, and Organization Minitab Project Files (*.MPJ) vs.
More informationTIMSS ADVANCED 2015 USER GUIDE FOR THE INTERNATIONAL DATABASE. Pierre Foy
TIMSS ADVANCED 2015 USER GUIDE FOR THE INTERNATIONAL DATABASE Pierre Foy TIMSS Advanced 2015 orks User Guide for the International Database Pierre Foy Contributors: Victoria A.S. Centurino, Kerry E. Cotter,
More informationWorking Paper: Do First Impressions Matter? Improvement in Early Career Teacher Effectiveness Allison Atteberry 1, Susanna Loeb 2, James Wyckoff 1
Center on Education Policy and Workforce Competitiveness Working Paper: Do First Impressions Matter? Improvement in Early Career Teacher Effectiveness Allison Atteberry 1, Susanna Loeb 2, James Wyckoff
More informationEvaluation of Teach For America:
EA15-536-2 Evaluation of Teach For America: 2014-2015 Department of Evaluation and Assessment Mike Miles Superintendent of Schools This page is intentionally left blank. ii Evaluation of Teach For America:
More informationDeveloping an Assessment Plan to Learn About Student Learning
Developing an Assessment Plan to Learn About Student Learning By Peggy L. Maki, Senior Scholar, Assessing for Learning American Association for Higher Education (pre-publication version of article that
More informationSchool Size and the Quality of Teaching and Learning
School Size and the Quality of Teaching and Learning An Analysis of Relationships between School Size and Assessments of Factors Related to the Quality of Teaching and Learning in Primary Schools Undertaken
More informationSociology 521: Social Statistics and Quantitative Methods I Spring Wed. 2 5, Kap 305 Computer Lab. Course Website
Sociology 521: Social Statistics and Quantitative Methods I Spring 2012 Wed. 2 5, Kap 305 Computer Lab Instructor: Tim Biblarz Office hours (Kap 352): W, 5 6pm, F, 10 11, and by appointment (213) 740 3547;
More informationEssentials of Ability Testing. Joni Lakin Assistant Professor Educational Foundations, Leadership, and Technology
Essentials of Ability Testing Joni Lakin Assistant Professor Educational Foundations, Leadership, and Technology Basic Topics Why do we administer ability tests? What do ability tests measure? How are
More informationSTT 231 Test 1. Fill in the Letter of Your Choice to Each Question in the Scantron. Each question is worth 2 point.
STT 231 Test 1 Fill in the Letter of Your Choice to Each Question in the Scantron. Each question is worth 2 point. 1. A professor has kept records on grades that students have earned in his class. If he
More informationPM tutor. Estimate Activity Durations Part 2. Presented by Dipo Tepede, PMP, SSBB, MBA. Empowering Excellence. Powered by POeT Solvers Limited
PM tutor Empowering Excellence Estimate Activity Durations Part 2 Presented by Dipo Tepede, PMP, SSBB, MBA This presentation is copyright 2009 by POeT Solvers Limited. All rights reserved. This presentation
More informationKnowledge management styles and performance: a knowledge space model from both theoretical and empirical perspectives
University of Wollongong Research Online University of Wollongong Thesis Collection University of Wollongong Thesis Collections 2004 Knowledge management styles and performance: a knowledge space model
More informationDublin City Schools Mathematics Graded Course of Study GRADE 4
I. Content Standard: Number, Number Sense and Operations Standard Students demonstrate number sense, including an understanding of number systems and reasonable estimates using paper and pencil, technology-supported
More informationDOCTORAL SCHOOL TRAINING AND DEVELOPMENT PROGRAMME
The following resources are currently available: DOCTORAL SCHOOL TRAINING AND DEVELOPMENT PROGRAMME 2016-17 What is the Doctoral School? The main purpose of the Doctoral School is to enhance your experience
More informationM55205-Mastering Microsoft Project 2016
M55205-Mastering Microsoft Project 2016 Course Number: M55205 Category: Desktop Applications Duration: 3 days Certification: Exam 70-343 Overview This three-day, instructor-led course is intended for individuals
More informationAlgebra 2- Semester 2 Review
Name Block Date Algebra 2- Semester 2 Review Non-Calculator 5.4 1. Consider the function f x 1 x 2. a) Describe the transformation of the graph of y 1 x. b) Identify the asymptotes. c) What is the domain
More informationEditor s Welcome. Summer 2016 Lean Six Sigma Innovation. You Deserve More. Lean Innovation: The Art of Making Less Into More
Summer 2016 Lean Six Sigma Innovation Editor s Welcome Lean Innovation: The Art of Making Less Into More Continuous improvement in business is about more than just a set of operational principles to increase
More informationBook Review: Build Lean: Transforming construction using Lean Thinking by Adrian Terry & Stuart Smith
Howell, Greg (2011) Book Review: Build Lean: Transforming construction using Lean Thinking by Adrian Terry & Stuart Smith. Lean Construction Journal 2011 pp 3-8 Book Review: Build Lean: Transforming construction
More informationGenerating Test Cases From Use Cases
1 of 13 1/10/2007 10:41 AM Generating Test Cases From Use Cases by Jim Heumann Requirements Management Evangelist Rational Software pdf (155 K) In many organizations, software testing accounts for 30 to
More informationDiagnostic Test. Middle School Mathematics
Diagnostic Test Middle School Mathematics Copyright 2010 XAMonline, Inc. All rights reserved. No part of the material protected by this copyright notice may be reproduced or utilized in any form or by
More informationMathematics process categories
Mathematics process categories All of the UK curricula define multiple categories of mathematical proficiency that require students to be able to use and apply mathematics, beyond simple recall of facts
More informationMathematics subject curriculum
Mathematics subject curriculum Dette er ei omsetjing av den fastsette læreplanteksten. Læreplanen er fastsett på Nynorsk Established as a Regulation by the Ministry of Education and Research on 24 June
More informationMath 96: Intermediate Algebra in Context
: Intermediate Algebra in Context Syllabus Spring Quarter 2016 Daily, 9:20 10:30am Instructor: Lauri Lindberg Office Hours@ tutoring: Tutoring Center (CAS-504) 8 9am & 1 2pm daily STEM (Math) Center (RAI-338)
More informationHonors Mathematics. Introduction and Definition of Honors Mathematics
Honors Mathematics Introduction and Definition of Honors Mathematics Honors Mathematics courses are intended to be more challenging than standard courses and provide multiple opportunities for students
More informationA. What is research? B. Types of research
A. What is research? Research = the process of finding solutions to a problem after a thorough study and analysis (Sekaran, 2006). Research = systematic inquiry that provides information to guide decision
More informationEntrepreneurial Discovery and the Demmert/Klein Experiment: Additional Evidence from Germany
Entrepreneurial Discovery and the Demmert/Klein Experiment: Additional Evidence from Germany Jana Kitzmann and Dirk Schiereck, Endowed Chair for Banking and Finance, EUROPEAN BUSINESS SCHOOL, International
More informationAnalysis of Enzyme Kinetic Data
Analysis of Enzyme Kinetic Data To Marilú Analysis of Enzyme Kinetic Data ATHEL CORNISH-BOWDEN Directeur de Recherche Émérite, Centre National de la Recherche Scientifique, Marseilles OXFORD UNIVERSITY
More informationThe CTQ Flowdown as a Conceptual Model of Project Objectives
The CTQ Flowdown as a Conceptual Model of Project Objectives HENK DE KONING AND JEROEN DE MAST INSTITUTE FOR BUSINESS AND INDUSTRIAL STATISTICS OF THE UNIVERSITY OF AMSTERDAM (IBIS UVA) 2007, ASQ The purpose
More informationGCSE Mathematics B (Linear) Mark Scheme for November Component J567/04: Mathematics Paper 4 (Higher) General Certificate of Secondary Education
GCSE Mathematics B (Linear) Component J567/04: Mathematics Paper 4 (Higher) General Certificate of Secondary Education Mark Scheme for November 2014 Oxford Cambridge and RSA Examinations OCR (Oxford Cambridge
More informationSpeech Recognition at ICSI: Broadcast News and beyond
Speech Recognition at ICSI: Broadcast News and beyond Dan Ellis International Computer Science Institute, Berkeley CA Outline 1 2 3 The DARPA Broadcast News task Aspects of ICSI
More informationPROFESSIONAL TREATMENT OF TEACHERS AND STUDENT ACADEMIC ACHIEVEMENT. James B. Chapman. Dissertation submitted to the Faculty of the Virginia
PROFESSIONAL TREATMENT OF TEACHERS AND STUDENT ACADEMIC ACHIEVEMENT by James B. Chapman Dissertation submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfillment
More informationFIGURE IT OUT! MIDDLE SCHOOL TASKS. Texas Performance Standards Project
FIGURE IT OUT! MIDDLE SCHOOL TASKS π 3 cot(πx) a + b = c sinθ MATHEMATICS 8 GRADE 8 This guide links the Figure It Out! unit to the Texas Essential Knowledge and Skills (TEKS) for eighth graders. Figure
More informationDocument number: 2013/ Programs Committee 6/2014 (July) Agenda Item 42.0 Bachelor of Engineering with Honours in Software Engineering
Document number: 2013/0006139 Programs Committee 6/2014 (July) Agenda Item 42.0 Bachelor of Engineering with Honours in Software Engineering Program Learning Outcomes Threshold Learning Outcomes for Engineering
More informationREADY TO WORK PROGRAM INSTRUCTOR GUIDE PART I
READY TO WORK PROGRAM INSTRUCTOR GUIDE PART I LESSON TITLE: Problem Solving Tools Method: Informal Lecture, Guided Discussion EDUCATIONAL OBJECTIVE: Comprehend the many different uses of quality/problem
More informationSAP EDUCATION SAMPLE QUESTIONS: C_TPLM40_65. Questions. In the audit structure, what can link an audit and a quality notification?
SAP EDUCATION SAMPLE QUESTIONS: C_TPLM40_65 SAP Certified Application Associate Quality Management with SAP ERP 6.0 EhP5 Disclaimer: These sample questions are for self-evaluation purposes only and do
More informationAGRICULTURAL AND EXTENSION EDUCATION
Agricultural and Extension 1 AGRICULTURAL AND EXTENSION EDUCATION Undergraduate Program Information The department offers a broad-based curriculum with majors, options and minors that prepare students
More informationMeasurement. When Smaller Is Better. Activity:
Measurement Activity: TEKS: When Smaller Is Better (6.8) Measurement. The student solves application problems involving estimation and measurement of length, area, time, temperature, volume, weight, and
More informationOn Human Computer Interaction, HCI. Dr. Saif al Zahir Electrical and Computer Engineering Department UBC
On Human Computer Interaction, HCI Dr. Saif al Zahir Electrical and Computer Engineering Department UBC Human Computer Interaction HCI HCI is the study of people, computer technology, and the ways these
More information(Sub)Gradient Descent
(Sub)Gradient Descent CMSC 422 MARINE CARPUAT marine@cs.umd.edu Figures credit: Piyush Rai Logistics Midterm is on Thursday 3/24 during class time closed book/internet/etc, one page of notes. will include
More informationTHE PENNSYLVANIA STATE UNIVERSITY SCHREYER HONORS COLLEGE DEPARTMENT OF MATHEMATICS ASSESSING THE EFFECTIVENESS OF MULTIPLE CHOICE MATH TESTS
THE PENNSYLVANIA STATE UNIVERSITY SCHREYER HONORS COLLEGE DEPARTMENT OF MATHEMATICS ASSESSING THE EFFECTIVENESS OF MULTIPLE CHOICE MATH TESTS ELIZABETH ANNE SOMERS Spring 2011 A thesis submitted in partial
More informationColorado State University Department of Construction Management. Assessment Results and Action Plans
Colorado State University Department of Construction Management Assessment Results and Action Plans Updated: Spring 2015 Table of Contents Table of Contents... 2 List of Tables... 3 Table of Figures...
More informationSchool of Innovative Technologies and Engineering
School of Innovative Technologies and Engineering Department of Applied Mathematical Sciences Proficiency Course in MATLAB COURSE DOCUMENT VERSION 1.0 PCMv1.0 July 2012 University of Technology, Mauritius
More informationEDEXCEL FUNCTIONAL SKILLS PILOT. Maths Level 2. Chapter 7. Working with probability
Working with probability 7 EDEXCEL FUNCTIONAL SKILLS PILOT Maths Level 2 Chapter 7 Working with probability SECTION K 1 Measuring probability 109 2 Experimental probability 111 3 Using tables to find the
More informationQuantitative analysis with statistics (and ponies) (Some slides, pony-based examples from Blase Ur)
Quantitative analysis with statistics (and ponies) (Some slides, pony-based examples from Blase Ur) 1 Interviews, diary studies Start stats Thursday: Ethics/IRB Tuesday: More stats New homework is available
More informationProficiency Illusion
KINGSBURY RESEARCH CENTER Proficiency Illusion Deborah Adkins, MS 1 Partnering to Help All Kids Learn NWEA.org 503.624.1951 121 NW Everett St., Portland, OR 97209 Executive Summary At the heart of the
More informationlearning collegiate assessment]
[ collegiate learning assessment] INSTITUTIONAL REPORT 2005 2006 Kalamazoo College council for aid to education 215 lexington avenue floor 21 new york new york 10016-6023 p 212.217.0700 f 212.661.9766
More informationThe Good Judgment Project: A large scale test of different methods of combining expert predictions
The Good Judgment Project: A large scale test of different methods of combining expert predictions Lyle Ungar, Barb Mellors, Jon Baron, Phil Tetlock, Jaime Ramos, Sam Swift The University of Pennsylvania
More informationSociology 521: Social Statistics and Quantitative Methods I Spring 2013 Mondays 2 5pm Kap 305 Computer Lab. Course Website
Sociology 521: Social Statistics and Quantitative Methods I Spring 2013 Mondays 2 5pm Kap 305 Computer Lab Instructor: Tim Biblarz Office: Hazel Stanley Hall (HSH) Room 210 Office hours: Mon, 5 6pm, F,
More informationOklahoma State University Policy and Procedures
Oklahoma State University Policy and Procedures GUIDELINES TO GOVERN WORKLOAD ASSIGNMENTS OF FACULTY MEMBERS 2-0110 ACADEMIC AFFAIRS August 2014 INTRODUCTION 1.01 Oklahoma State University, as a comprehensive
More information