Problem Solving and Data Analysis Using Minitab (ePub)
A Clear and Easy Guide to Six Sigma Methodology
(Sprache: Englisch)
Six Sigma statistical methodology using Minitab
Problem Solving and Data Analysis using Minitab presents example-based learning to aid readers in understanding how to use MINITAB 16 for statistical analysis and problem solving. Each example and exercise...
Problem Solving and Data Analysis using Minitab presents example-based learning to aid readers in understanding how to use MINITAB 16 for statistical analysis and problem solving. Each example and exercise...
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Produktinformationen zu „Problem Solving and Data Analysis Using Minitab (ePub)“
Six Sigma statistical methodology using Minitab
Problem Solving and Data Analysis using Minitab presents example-based learning to aid readers in understanding how to use MINITAB 16 for statistical analysis and problem solving. Each example and exercise is broken down into the exact steps that must be followed in order to take the reader through key learning points and work through complex analyses. Exercises are featured at the end of each example so that the reader can be assured that they have understood the key learning points.
Key features:
* Provides readers with a step by step guide to problem solving and statistical analysis using Minitab 16 which is also compatible with version 15.
* Includes fully worked examples with graphics showing menu selections and Minitab outputs.
* Uses example based learning that the reader can work through at their pace.
* Contains hundreds of screenshots to aid the reader, along with explanations of the statistics being performed and interpretation of results.
* Presents the core statistical techniques used by Six Sigma Black Belts.
* Contains examples, exercises and solutions throughout, and is supported by an accompanying website featuring the numerous example data sets.
Making Six Sigma statistical methodology accessible to beginners, this book is aimed at numerical professionals, students or academics who wish to learn and apply statistical techniques for problem solving, process improvement or data analysis whilst keeping mathematical theory to a minimum.
Problem Solving and Data Analysis using Minitab presents example-based learning to aid readers in understanding how to use MINITAB 16 for statistical analysis and problem solving. Each example and exercise is broken down into the exact steps that must be followed in order to take the reader through key learning points and work through complex analyses. Exercises are featured at the end of each example so that the reader can be assured that they have understood the key learning points.
Key features:
* Provides readers with a step by step guide to problem solving and statistical analysis using Minitab 16 which is also compatible with version 15.
* Includes fully worked examples with graphics showing menu selections and Minitab outputs.
* Uses example based learning that the reader can work through at their pace.
* Contains hundreds of screenshots to aid the reader, along with explanations of the statistics being performed and interpretation of results.
* Presents the core statistical techniques used by Six Sigma Black Belts.
* Contains examples, exercises and solutions throughout, and is supported by an accompanying website featuring the numerous example data sets.
Making Six Sigma statistical methodology accessible to beginners, this book is aimed at numerical professionals, students or academics who wish to learn and apply statistical techniques for problem solving, process improvement or data analysis whilst keeping mathematical theory to a minimum.
Inhaltsverzeichnis zu „Problem Solving and Data Analysis Using Minitab (ePub)“
Chapter 1 Introduction Chapter 2 Minitab Navigation 2.1 Windows 2.2 Dropdown Menus 2.3 Importing Data 2.4 Column Formats 2.5 The Calculator 2.6 Basic Graphs 2.7 Adding Detail to Graphs 2.8 Saving Graphs 2.9 Dotplots 2.10 Using the Brush 2.11 Boxplots 2.12 Bar Charts 2.13 The Layout Tool 2.14 Producing Graphs with the Assistant 2.15 Producing Reports 2.16 Creating a New Project/Worksheet Button Chapter 3 Basic Statistics 3.1 Types of Data 3.2 Central Location 3.3 Dispersion 3.4 Descriptive Statistics 3.5 Inferential Statistics 3.6 Confidence Intervals 3.7 Normal Distribution 3.8 Deviations from Normality 3.9 Central Limit Theorem Chapter 4 Hypothesis Testing 4.1 The Problem Statement 4.2 Null and Alternate Hypotheses 4.3 Establishing the Risks 4.4 Power and Sample Size 4.5 Conducting the Test and Evaluating the Results 4.6 One Sample t Test 4.7 Paired t Test 4.8 Two Variance Test 4.9 Two Sample t Test Chapter 5 Analysis of Variance 5.1 How ANOVA Works 5.2 One Way ANOVA (Classic) 5.3 One Way ANOVA with the Assistant 5.4 ANOVA General Linear Model Chapter 6 Measurement System Analysis 6.1 The Importance of Measurement Systems 6.2 How Measurement Systems Affect Data 6.3 Analysing the Appropriate Systems 6.4 Types of Measurement Systems Error 6.5 Measurement Systems Toolbox 6.6 Type 1 Gage Study 6.7 Gage Repeatability and Reproducibility Studies 6.8 Create Gage R&R Study 6.9 Gage R&R (Crossed) 6.10 Gage R&R Crossed Studies 6.11 Gage R&R (Crossed) Study 6.12 Gage R&R (Nested) 6.13 Gage Bias and Linearity Study Chapter 7 Statistical Process Control 7.1 The Origins of Statistical Process Control 7.2 Common Cause and Special Cause Variation 7.3 Detection Rules for Special Causes 7.4 False Alarms 7.5 When Should We Use SPC Charts? 7.6 Subgrouping 7.7 The Appropriate Chart 7.8 The I-MR Chart 7.9 The Xbar-R Chart 7.10 The Xbar-S Chart 7.11 SPC Exercise 7.12 The I-MR-R/S Chart Chapter 8 Process Capability 8.1 The Basics of Process Capability 8.2 Short Term and Overall Capability
... mehr
8.3 Capability Analysis for Normal Data 8.4 Capability Analysis for Non Normal Data 8.5 Capability Comparison using the Assistant Chapter 9 Correlation and Regression 9.1 What are Correlation and Regression? 9.2 Correlation 9.3 Multiple Correlations 9.4 Introduction to Regression 9.5 Single Predictor Regression 9.6 Introduction to Multiple Predictor Regression 9.7 Multiple Predictor Regression 9.8 Predictor Selection Procedure 9.9 Nonlinear Regression Chapter 10 Design of Experiment 10.1 Why Use Design of Experiment? 10.2 Types of DOE 10.3 DOE Terminology 10.4 Two Level Factorial Designs 10.5 Fractional Factorial Chapter 11 Help 11.1 Help Overview 11.2 Help! Help! 11.3 Tutorials 11.4 StatGuide 11.5 Methods and Formulas 11.6 Meet Minitab 11.7 Help on the Web 11.8 Help on the Web and Datasets 11.9 Datasets Index
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Autoren-Porträt von Rehman M. Khan
Rehman M. Khan, Chartered Chemical Engineer and Six Sigma Black Belt, Loughbourough, UK.
Bibliographische Angaben
- Autor: Rehman M. Khan
- 2013, 1. Auflage, 488 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 1118307526
- ISBN-13: 9781118307526
- Erscheinungsdatum: 28.01.2013
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: ePub
- Größe: 78 MB
- Mit Kopierschutz
Sprache:
Englisch
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