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Informationen zum Autor G. Robin Henderson, Statistical Consultant, Halcro Consultancy. Klappentext This book aims to enable readers to understand and implement, via the widely used statistical software package Minitab (Release 16), statistical methods fundamental to the Six Sigma approach to the continuous improvement of products, processes and services.The second edition includes the following new material:* Pareto charts and Cause-and-Effect diagrams* Time-weighted control charts cumulative sum (CUSUM) and exponentially weighted moving average (EWMA)* Multivariate control charts* Acceptance sampling by attributes and variables (not provided in Release 14)* Tests of association using the chi-square distribution* Logistic regression* Taguchi experimental designs Zusammenfassung This book aims to enable readers to understand and implement, via the widely used statistical software package Minitab (Release 16), statistical methods fundamental to the Six Sigma approach to the continuous improvement of products, processes and services.The second edition includes the following new material:* Pareto charts and Cause-and-Effect diagrams* Time-weighted control charts cumulative sum (CUSUM) and exponentially weighted moving average (EWMA)* Multivariate control charts* Acceptance sampling by attributes and variables (not provided in Release 14)* Tests of association using the chi-square distribution* Logistic regression* Taguchi experimental designs Inhaltsverzeichnis Foreword. Preface. Acknowledgements. About the Author. 1 Introduction. 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 Data Display, Summary and Manipulation. 2.1 The Run Chart - a First Minitab Session. 2.1.1 Input of Data Via Keyboard and Creation of a Run Chart in Minitab. 2.1.2 Minitab Projects and Their Components. 2.2 Display and Summary of Univariate Data. 2.2.1 Histogram and Distribution. 2.2.2 Shape of a Distribution. 2.2.3 Location. 2.2.4 Variability. 2.3 Data Input, Output, Manipulation and Management. 2.3.1 Data Input and Output. 2.3.2 Stacking and Unstacking of Data; Changing Data Type and Coding. 2.3.3 Case Study Demonstrating Ranking, Sorting and Extraction of Information from Date/Time Data. 2.4 Exercises and Follow-Up Activities. 3 Exploratory Data Analysis, Display and Summary of Multivariate Data. 3.1 Exploratory Data Analysis. 3.1.1 Stem-and-Leaf Displays. 3.1.2 Outliers and Outlier Detection. 3.1.3 Boxplots. 3.1.4 Brushing. 3.2 Display and Summary of Bivariate and Multivariate Data. 3.2.1 Bivariate Data - Scatterplots and Marginal Plots. 3.2.2 Covariance and Correlation. 3.2.3 Multivariate Data - Matrix Plots. 3.2.4 Multi-Vari Charts. 3.3 Other Displays. 3.3.1 Pareto Charts. 3.3.2 Cause-and-Effect Diagrams. 3.4 Exercises and Follow-Up Activities. 4 Statistical Models. 4.1 Fundamentals of Probability. 4.1.1 Concept and Notation. 4.1.2 Rules for Probabilities. 4.2 Probability Distributions for Counts and Measurements. 4.2.1 Binomial Distribution. 4.2.2 Poisson Distribution. 4.2.3 Normal (Gaussian) Distribution. 4.3 Distribution of Means and Proportions. 4.3.1 Two Preliminary Results. 4.3.2 Distribution of the Sample Mean. 4.3.3 Distribution of the Sample Proportion. 4.4 Multivariate Normal Distribution. 4.5 Statistical Models Applied to Acceptance Sampling. 4.5.1 Acceptance Sampli...
