Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented.
Industrial Statistics with MINITAB:
- Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry.
- Explores statistical techniques and how they can be used effectively with the help of MINITAB 16.
- Contains extensive illustrative examples and case studies throughout and assumes no previous statistical knowledge.
- Emphasises data graphics and visualization, and the most used industrial statistical tools, such as Statistical Process Control and Design of Experiments.
- Is supported by an accompanying website featuring case studies and the corresponding datasets.
Six Sigma Green Belts and Black Belts will find explanations and examples of the most relevant techniques in DMAIC projects. The book can also be used as quick reference enabling the reader to be confident enough to explore other MINITAB capabilities.
Table of Contents
PART ONE INTRODUCTION AND GRAPHICAL TECHNIQUES 1
1 A First Look 3
2 Graphics for Univariate Data 15
3 Pareto Charts and Cause–Effect Diagrams 31
4 Scatterplots 37
5 Three Dimensional Plots 52
6 Part One: Case Studies – Introduction and Graphical Techniques 62
PART TWO HYPOTHESIS TESTING. COMPARISON OF TREATMENTS 79
7 Random Numbers and Numbers Following a Pattern 81
8 Computing Probabilities 87
9 Hypothesis Testing for Means and Proportions. Normality Test 95
10 Comparison of Two Means, Two Variances or Two Proportions 103
11 Comparison of More than Two Means: Analysis of Variance 110
12 Part Two: Case Studies – Hypothesis Testing. Comparison of Treatments 120
PART THREE MEASUREMENT SYSTEMS STUDIES AND CAPABILITY STUDIES 137
13 Measurement System Study 139
14 Capability Studies 151
15 Capability Studies for Attributes 163
16 Part Three: Case Studies – R&R Studies and Capability Studies 168
PART FOUR MULTI-VARI CHARTS AND STATISTICAL PROCESS CONTROL 181
17 Multi-Vari Charts 183
18 Control Charts I: Individual Observations 188
19 Control Charts II: Means and Ranges 198
20 Control Charts for Attributes 204
21 Part Four: Case Studies – Multi-Vari Charts and Statistical Process Control 212
PART FIVE REGRESSION AND MULTIVARIATE ANALYSIS 231
22 Correlation and Simple Regression 235
23 Multiple Regression 247
24 Multivariate Analysis 256
25 Part Five: Case Studies – Regression and Multivariate Analysis 272
PART SIX EXPERIMENTAL DESIGN AND RELIABILITY 293
26 Factorial Designs: Creation 295
27 Factorial Designs: Analysis 303
28 Response Surface Methodology 313
29 Reliability 325
30 Part Six: Case Studies – Design of Experiments and Reliability 335
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