About the author.
1.1 Quality and quality improvement.
1.2 Six Sigma quality improvement.
1.3 The Six Sigma roadmap and DMAIC.
1.4 The role of statistical methods in Six Sigma.
1.5 MINITAB and its role in the implementation of statistical methods.
1.6 Exercises and follow-up activities.
2 Introduction to MINITAB, data display, summary and manipulation.
2.1 The run chart – a first MINITAB session.
2.2 Display and summary of univariate data.
2.3 Data input, output, manipulation and management.
2.4 Exercises and follow-up activities.
3 Exploratory data analysis, display and summary of multivariate data.
3.1 Exploratory data analysis.
3.2 Display and summary of bivariate and multivariate data.
3.3 Exercises and follow-up activities.
4 Statistical models.
4.1 Fundamentals of probability.
4.2 Probability distributions for counts and measurements.
4.3 Distribution of means and proportions.
4.4 Exercises and follow-up activities.
5 Control charts.
5.1 Shewhart charts for measurement data.
5.2 Shewhart charts for attribute data.
5.3 Process adjustment.
5.4 Exercises and follow-up activities.
6 Process capability analysis.
6.1 Process capability.
6.2 Exercises and follow-up activities.
7 Process experimentation with a single factor.
7.1 Fundamental concepts in hypothesis testing.
7.2 Tests and confidence intervals for the comparison of means and of proportions with a standard.
7.3 Tests and confidence intervals for the comparison of two means or two proportions.
7.4 The analysis of paired data – t-tests and sign tests.
7.5 Experiments with a single factor having more than two levels.
7.6 Blocking in single–factor experiments.
7.7 Experiments with a single factor, with more than two levels, where the response is a proportion.
7.8 Tests for equality of variance.
7.9 Exercises and follow-up activities.
8 Process experimentation with two or more factors.
8.1 General factorial experiments.
8.2 Full factorial experiments in the 2k series.
8.3 Fractional factorial experiments in the 2k–p series.
8.4 Exercises and follow-up activities.
9 Evaluation of measurement processes.
9.1 Measurement process concepts.
9.2 Gauge repeatability and reproducibility (R&R) studies.
9.3 Attribute scenarios.
9.4 Exercises and follow-up activities.
10 Regression and model building.
10.1 Regression with a single predictor variable.
10.2 Multiple regression.
10.3 Response surface methods.
10.4 Exercises and follow-up activities.
11 More about MINITAB.
11.1 Learning more about MINITAB and obtaining help.
11.3 Further MINITAB.