Statistics and probability with applications for engineers and scientists using Minitab, R and JMP
Author
Published
Hoboken, NJ : John Wiley & Sons, Inc., 2020.
Status
Available Online
Description
Introduces basic concepts in probability and statistics to data science students, as well as engineers and scientists
Aimed at undergraduate/graduate-level engineering and natural science students, this timely, fully updated edition of a popular book on statistics and probability shows how real-world problems can be solved using statistical concepts. It removes Excel exhibits and replaces them with R software throughout, and updates both MINITAB and JMP software instructions and content. A new chapter discussing data mining—including big data, classification, machine learning, and visualization—is featured. Another new chapter covers cluster analysis methodologies in hierarchical, nonhierarchical, and model based clustering. The book also offers a chapter on Response Surfaces that previously appeared on the book’s companion website.
Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP, Second Edition is broken into two parts. Part I covers topics such as: describing data graphically and numerically, elements of probability, discrete and continuous random variables and their probability distributions, distribution functions of random variables, sampling distributions, estimation of population parameters and hypothesis testing. Part II covers: elements of reliability theory, data mining, cluster analysis, analysis of categorical data, nonparametric tests, simple and multiple linear regression analysis, analysis of variance, factorial designs, response surfaces, and statistical quality control (SQC) including phase I and phase II control charts. The appendices contain statistical tables and charts and answers to selected problems.
- Features two new chapters—one on Data Mining and another on Cluster Analysis
- Now contains R exhibits including code, graphical display, and some results
- MINITAB and JMP have been updated to their latest versions
- Emphasizes the p-value approach and includes related practical interpretations
- Offers a more applied statistical focus, and features modified examples to better exhibit statistical concepts
- Supplemented with an Instructor's-only solutions manual on a book’s companion website
Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP is an excellent text for graduate level data science students, and engineers and scientists. It is also an ideal introduction to applied statistics and probability for undergraduate students in engineering and the natural sciences.
More Details
Format
Edition
Second edition.
Language
English
ISBN
9781119516620, 1119516625, 9781119516644, 1119516641, 9781119516651, 111951665X
UPC
9781119516637
Notes
General Note
Revision of: Statistics and probability with applications for engineers and scientists. 2013.
Bibliography
Includes bibliographical references and index.
Description
"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"-- Provided by publisher.
Local note
O'Reilly O'Reilly Online Learning: Academic/Public Library Edition
Table of Contents
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
2.6.2 Median of a Grouped Data
2.6.3 Mode of a Grouped Data
2.6.4 Variance of a Grouped Data
2.7 Measures of Relative Position
2.7.1 Percentiles
2.7.2 Quartiles
2.7.3 Interquartile Range (IQR)
2.7.4 Coefficient of Variation
2.8 Box-Whisker Plot
2.8.1 Construction of a Box Plot
2.8.2 How to Use the Box Plot
2.9 Measures of Association
2.10 Case Studies
2.10.1 About St. Luke's Hospital
2.11 Using JMP
2.11 Review Practice Problems
Chapter 3 Elements of Probability
3.1 Introduction
3.2 Random Experiments, Sample Spaces, and Events
3.2.1 Random Experiments and Sample Spaces
3.2.2 Events
3.3 Concepts of Probability
3.4 Techniques of Counting Sample Points
3.4.1 Tree Diagram
3.4.2 Permutations
3.4.3 Combinations
3.4.4 Arrangements of n Objects Involving Several Kinds of Objects
3.5 Conditional Probability
3.6 Bayes's Theorem
3.7 Introducing Random Variables
3.7 Review Practice Problems
Chapter 4 Discrete Random Variables and Some Important Discrete Probability Distributions
4.1 Graphical Descriptions of Discrete Distributions
4.2 Mean and Variance of a Discrete Random Variable
4.2.1 Expected Value of Discrete Random Variables and Their Functions
4.2.2 The Moment-Generating Function-Expected Value of a Special Function of X
4.3 The Discrete Uniform Distribution
4.4 The Hypergeometric Distribution
4.5 The Bernoulli Distribution
4.6 The Binomial Distribution
4.7 The Multinomial Distribution
4.8 The Poisson Distribution
4.8.1 Definition and Properties of the Poisson Distribution
4.8.2 Poisson Process
4.8.3 Poisson Distribution as a Limiting Form of the Binomial
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Citations
APA Citation, 7th Edition (style guide)
Gupta, B. C., Guttman, I., & Jayalath, K. (2020). Statistics and probability with applications for engineers and scientists using Minitab, R and JMP (Second edition.). John Wiley & Sons, Inc..
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Gupta, Bhisham C., 1942-, Irwin, Guttman and Kalanka, Jayalath. 2020. Statistics and Probability With Applications for Engineers and Scientists Using Minitab, R and JMP. Hoboken, NJ: John Wiley & Sons, Inc.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Gupta, Bhisham C., 1942-, Irwin, Guttman and Kalanka, Jayalath. Statistics and Probability With Applications for Engineers and Scientists Using Minitab, R and JMP Hoboken, NJ: John Wiley & Sons, Inc, 2020.
Harvard Citation (style guide)Gupta, B. C., Guttman, I. and Jayalath, K. (2020). Statistics and probability with applications for engineers and scientists using minitab, R and JMP. Second edn. Hoboken, NJ: John Wiley & Sons, Inc.
MLA Citation, 9th Edition (style guide)Gupta, Bhisham C., Irwin Guttman, and Kalanka Jayalath. Statistics and Probability With Applications for Engineers and Scientists Using Minitab, R and JMP Second edition., John Wiley & Sons, Inc., 2020.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
Staff View
Grouped Work ID
846715e2-e1c7-df1e-f002-c2b7e07b1c61-eng
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| Author | gupta bhisham c |
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| Last Update | 2025-01-24 12:33:29PM |
| Last Indexed | 2025-03-27 03:20:29AM |
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| 240 | 1 | 0 | |a Statistics and probability with applications for engineers and scientists |
| 245 | 1 | 0 | |a Statistics and probability with applications for engineers and scientists using Minitab, R and JMP /|c Bhisham C. Gupta, Irwin Guttman, Kalanka P. Jayalath. |
| 250 | |a Second edition. | ||
| 264 | 1 | |a Hoboken, NJ :|b John Wiley & Sons, Inc.,|c 2020. | |
| 264 | 4 | |c ©2020 | |
| 300 | |a 1 online resource | ||
| 336 | |a text|b txt|2 rdacontent | ||
| 337 | |a computer|b c|2 rdamedia | ||
| 338 | |a online resource|b cr|2 rdacarrier | ||
| 347 | |a text file | ||
| 347 | |a text file|2 rda | ||
| 500 | |a Revision of: Statistics and probability with applications for engineers and scientists. 2013. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 2.6.1 Mean of a Grouped Data -- 2.6.2 Median of a Grouped Data -- 2.6.3 Mode of a Grouped Data -- 2.6.4 Variance of a Grouped Data -- 2.7 Measures of Relative Position -- 2.7.1 Percentiles -- 2.7.2 Quartiles -- 2.7.3 Interquartile Range (IQR) -- 2.7.4 Coefficient of Variation -- 2.8 Box-Whisker Plot -- 2.8.1 Construction of a Box Plot -- 2.8.2 How to Use the Box Plot -- 2.9 Measures of Association -- 2.10 Case Studies -- 2.10.1 About St. Luke's Hospital -- 2.11 Using JMP -- 2.11 Review Practice Problems -- Chapter 3 Elements of Probability -- 3.1 Introduction | |
| 505 | 8 | |a 3.2 Random Experiments, Sample Spaces, and Events -- 3.2.1 Random Experiments and Sample Spaces -- 3.2.2 Events -- 3.3 Concepts of Probability -- 3.4 Techniques of Counting Sample Points -- 3.4.1 Tree Diagram -- 3.4.2 Permutations -- 3.4.3 Combinations -- 3.4.4 Arrangements of n Objects Involving Several Kinds of Objects -- 3.5 Conditional Probability -- 3.6 Bayes's Theorem -- 3.7 Introducing Random Variables -- 3.7 Review Practice Problems -- Chapter 4 Discrete Random Variables and Some Important Discrete Probability Distributions -- 4.1 Graphical Descriptions of Discrete Distributions | |
| 505 | 8 | |a 4.2 Mean and Variance of a Discrete Random Variable -- 4.2.1 Expected Value of Discrete Random Variables and Their Functions -- 4.2.2 The Moment-Generating Function-Expected Value of a Special Function of X -- 4.3 The Discrete Uniform Distribution -- 4.4 The Hypergeometric Distribution -- 4.5 The Bernoulli Distribution -- 4.6 The Binomial Distribution -- 4.7 The Multinomial Distribution -- 4.8 The Poisson Distribution -- 4.8.1 Definition and Properties of the Poisson Distribution -- 4.8.2 Poisson Process -- 4.8.3 Poisson Distribution as a Limiting Form of the Binomial | |
| 520 | |a "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"--|c Provided by publisher. | ||
| 542 | |f Copyright © 2020 by John Wiley & Sons|g 2020 | ||
| 588 | 0 | |a Online resource; title from digital title page (viewed on March 04, 2020). | |
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