http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Problem solving and data analysis using Minitab
a clear and easy guide to six sigma methodology
"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"--
Cover; Title Page; Copyright; Contents; Acknowledgements; 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 Statistics3.6 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 Analysis6.1 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 Worksheet; 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 Variation7.3 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 Designs; Chapter 11 Help; 11.1 Help Overview; 11.2 Help! Help!; 11.3 Tutorials; 11.4 StatGuide; 11.5 Methods and Formulas.
Chichester, West Sussex, United Kingdom : John Wiley & Sons Inc., 2013