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Problem Solving and Data Analysis Using Minitab : A Clear and Easy Guide to Six Sigma Methodology,9781118307571
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Problem Solving and Data Analysis Using Minitab : A Clear and Easy Guide to Six Sigma Methodology



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This is the edition with a publication date of 4/1/2013.

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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. The text contains hundreds of screenshots of the sequential inputs required to drive MINITAB, along with the outputs as well as concise explanation of the statistics being performed and interpretation of results.

Table of Contents

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

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


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