Statistics for Engineers and Scientists
Author | : William Cyrus Navidi |
Publisher | : McGraw-Hill |
Total Pages | : 936 |
Release | : 2008 |
Genre | : Bootstrap (Statistics) |
ISBN | : |
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Author | : William Cyrus Navidi |
Publisher | : McGraw-Hill |
Total Pages | : 936 |
Release | : 2008 |
Genre | : Bootstrap (Statistics) |
ISBN | : |
Author | : Nicholas P. Cheremisinoff |
Publisher | : CRC Press |
Total Pages | : 224 |
Release | : 2020-09-24 |
Genre | : Mathematics |
ISBN | : 1000125114 |
This book provides direction in constructing regression routines that can be used with worksheet software on personal computers. The book lists useful references for those readers who desire more in-depth understanding of the mathematical bases, and is helpful for science and engineering students.
Author | : Nicholas P. Cheremisinoff |
Publisher | : CRC Press |
Total Pages | : 228 |
Release | : 1987-11-26 |
Genre | : Mathematics |
ISBN | : 9780877625056 |
This book provides direction in constructing regression routines that can be used with worksheet software on personal computers. The book lists useful references for those readers who desire more in-depth understanding of the mathematical bases, and is helpful for science and engineering students.
Author | : Peter Bruce |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 395 |
Release | : 2017-05-10 |
Genre | : Computers |
ISBN | : 1491952911 |
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
Author | : NP. Cheremisinoff |
Publisher | : |
Total Pages | : |
Release | : 1987 |
Genre | : |
ISBN | : |
Author | : William Cyrus Navidi |
Publisher | : College Ie Overruns |
Total Pages | : 582 |
Release | : 2010 |
Genre | : Engineering |
ISBN | : 9780070166974 |
Principles of Statistics for Engineers and Scientists offers the same crystal clear presentation of applied statistics as Bill Navidi's Statistics for Engineers and Scientists text, in a manner especially designed for the needs of a one-semester course that is focused on applications. By presenting ideas in the context of real-world data sets and with plentiful examples of computer output, the book is great for motivating students to understand the importance of statistics in their careers and their lives. The text features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly and the use of contemporary real world data sets to help motivate students and show direct connections to industry and research. While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition.
Author | : Sheldon M. Ross |
Publisher | : |
Total Pages | : 532 |
Release | : 1987 |
Genre | : Mathematics |
ISBN | : |
Elements of probability; Random variables and expectation; Special; random variables; Sampling; Parameter estimation; Hypothesis testing; Regression; Analysis of variance; Goodness of fit and nonparametric testing; Life testing; Quality control; Simulation.
Author | : Bhisham C. Gupta |
Publisher | : John Wiley & Sons |
Total Pages | : 896 |
Release | : 2013-04-29 |
Genre | : Mathematics |
ISBN | : 1118464044 |
Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab® and Microsoft® Office Excel® to analyze various data sets. The book also features: • Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices • A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method • Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology • A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP ® routines and results Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.
Author | : Jim Morrison |
Publisher | : John Wiley & Sons |
Total Pages | : 192 |
Release | : 2009-06-15 |
Genre | : Mathematics |
ISBN | : 9780470746431 |
This practical text is an essential source of information for those wanting to know how to deal with the variability that exists in every engineering situation. Using typical engineering data, it presents the basic statistical methods that are relevant, in simple numerical terms. In addition, statistical terminology is translated into basic English. In the past, a lack of communication between engineers and statisticians, coupled with poor practical skills in quality management and statistical engineering, was damaging to products and to the economy. The disastrous consequence of setting tight tolerances without regard to the statistical aspect of process data is demonstrated. This book offers a solution, bridging the gap between statistical science and engineering technology to ensure that the engineers of today are better equipped to serve the manufacturing industry. Inside, you will find coverage on: the nature of variability, describing the use of formulae to pin down sources of variation; engineering design, research and development, demonstrating the methods that help prevent costly mistakes in the early stages of a new product; production, discussing the use of control charts, and; management and training, including directing and controlling the quality function. The Engineering section of the index identifies the role of engineering technology in the service of industrial quality management. The Statistics section identifies points in the text where statistical terminology is used in an explanatory context. Engineers working on the design and manufacturing of new products find this book invaluable as it develops a statistical method by which they can anticipate and resolve quality problems before launching into production. This book appeals to students in all areas of engineering and also managers concerned with the quality of manufactured products. Academic engineers can use this text to teach their students basic practical skills in quality management and statistical engineering, without getting involved in the complex mathematical theory of probability on which statistical science is dependent.
Author | : William C. Navidi |
Publisher | : McGraw-Hill Science, Engineering & Mathematics |
Total Pages | : 0 |
Release | : 2004-12 |
Genre | : Bootstrap (Statistics) |
ISBN | : 9780073107677 |
Statistics for Engineers and Scientists stands out for its crystal clear presentation of applied statistics. Suitable for a one or two semester course, the book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work. Statistics for Engineers and Scientists features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly, along with the use of contemporary real world data sets to help motivate students and show direct connections to industry and research. While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition.