Statistics and probability with applications for engineers and scientists using Minitab, R and JMP

"This new edition shows how real world problems can be solved using statistical concepts, now with many timely updates. The authors have included R software and removed the Excel exhibits throughout the book. The new Chapter 20 discusses data mining including topics in big data, classification, machine learning, and visualization. The new Chapter 21 covers cluster analysis methodologies including in hierarchical, nonhierarchical, and model based clustering. In addition, the authors have included a chapter on Response Surveys within the book, which was previously only available on the book's companion website. This book is broken into two parts. Part I covers topics such as: elements of probability, discrete random variables and some important discrete probability distributions, distribution functions of random variables, and estimation of population parameters. Part II covers: elements of reliability theory, statistical quality control, analysis of categorical data, and analysis of variance. The appendices contain statistical tables and charts and answers to selected problems"--

Revision of: Statistics and probability with applications for engineers and scientists. 2013.

Cover -- Title Page -- Copyright -- Contents -- Chapter 1 Introduction -- 1.1 Designed Experiment -- 1.1.1 Motivation for the Study -- 1.1.2 Investigation -- 1.1.3 Changing Criteria -- 1.1.4 A Summary of the Various Phases of the Investigation -- 1.2 A Survey -- 1.3 An Observational Study -- 1.4 A Set of Historical Data -- 1.5 A Brief Description of What is Covered in this Book -- Chapter 2 Describing Data Graphically and Numerically -- 2.1 Getting Started with Statistics -- 2.1.1 What Is Statistics? -- 2.1.2 Population and Sample in a Statistical Study

2.2 Classification of Various Types of Data -- 2.2.1 Nominal Data -- 2.2.2 Ordinal Data -- 2.2.3 Interval Data -- 2.2.4 Ratio Data -- 2.3 Frequency Distribution Tables for Qualitative and Quantitative Data -- 2.3.1 Qualitative Data -- 2.3.2 Quantitative Data -- 2.4 Graphical Description of Qualitative and Quantitative Data -- 2.4.1 Dot Plot -- 2.4.2 Pie Chart -- 2.4.3 Bar Chart -- 2.4.4 Histograms -- 2.4.5 Line Graph -- 2.4.6 Stem-and-Leaf Plot -- 2.5 Numerical Measures of Quantitative Data -- 2.5.1 Measures of Centrality -- 2.5.2 Measures of Dispersion -- 2.6 Numerical Measures of Grouped Data

2.6.1 Mean of a Grouped Data -- 2.6…