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Author : William Cyrus Navidi
Publisher : Unknown
Page : 582 pages
File Size : 48,7 Mb
Release : 2010
Category : Engineering
ISBN : 1283450348
Author : William Navidi
Publisher : Unknown
Page : 128 pages
File Size : 44,7 Mb
Release : 2020-02-04
Category : Electronic
ISBN : 1260570738
Author : William Cyrus Navidi
Publisher : Unknown
Page : 128 pages
File Size : 40,5 Mb
Release : 2021
Category : Electronic books
ISBN : 1260589471
"This book is based on the author's more comprehensive text Statistics for Engineers and Scientists, 2nd edition (McGraw-Hill, 2008), which is used for both one- and twosemester courses. The key concepts from that book form the basis for this text, which is designed for a one-semester course. The emphasis is on statistical methods and how they can be applied to problems in science and engineering, rather than on theory. While the fundamental principles of statistics are common to all disciplines, students in science and engineering learn best from examples that present important ideas in realistic settings. Accordingly, the book contains many examples that feature real, contemporary data sets, both to motivate students and to show connections to industry and scientific research. As the text emphasizes applications rather than theory, the mathematical level is appropriately modest. Most of the book will be mathematically accessible to those whose background includes one semester of calculus"--
Author : William Cyrus Navidi
Publisher : College Ie Overruns
Page : 582 pages
File Size : 40,6 Mb
Release : 2010
Category : Engineering
ISBN : 0070166978
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 : William Navidi
Publisher : Unknown
Page : 922 pages
File Size : 50,9 Mb
Release : 2019-03-29
Category : Bootstrap (Statistics)
ISBN : 1260547884
Author : William Navidi, Prof.
Publisher : McGraw-Hill Education
Page : 624 pages
File Size : 47,9 Mb
Release : 2020-01-27
Category : Technology & Engineering
ISBN : 1260442179
Available for the first time in McGraw-Hill's Connect! Principles of Statistics for Engineers and Scientists emphasizes statistical methods and how they can be applied to problems in science and engineering. The book contains many examples that feature real, contemporary data sets, both to motivate students and to show connections to industry and scientific research. Because statistical analyses are done on computers, the book contains exercises and examples that involve interpreting, as well as generating, computer output. This book may be used effectively with any software package.
Author : Sheldon M. Ross
Publisher : Unknown
Page : 532 pages
File Size : 52,9 Mb
Release : 1987
Category : Mathematics
ISBN : UOM:39015013026342
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 : Robert M. Bethea,Benjamin S. Duran,Thomas L. Boullion
Publisher : Unknown
Page : 740 pages
File Size : 55,7 Mb
Release : 1985
Category : Technology & Engineering
ISBN : UOM:39015047952349
Revised and expanded edition of a text that is intended as a basic introductory course in applied statistical methods for students of engineering and the physical sciences at the undergraduate level. Theoretical developments and mathematical treatment of the principles involved are included as needed for understanding of the validity of the techniques presented. The major changes in this edition are a new chapter on statistical process control and reliability, several added nonparametric techniques, and 30 added problems. Annotation copyright by Book News, Inc., Portland, OR
Author : Edward L. Robinson
Publisher : Princeton University Press
Page : 408 pages
File Size : 43,7 Mb
Release : 2016-10-04
Category : Science
ISBN : 9780691169927
Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix. Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. In-depth discussion of data analysis for scientists and engineers Coverage of both frequentist and Bayesian approaches to data analysis Extensive look at analysis techniques for time-series data and images Detailed exploration of linear and nonlinear modeling of data Emphasis on error analysis Instructor's manual (available only to professors)
Author : Milan Holický
Publisher : Springer Science & Business Media
Page : 181 pages
File Size : 42,6 Mb
Release : 2013-08-04
Category : Mathematics
ISBN : 9783642383007
The theory of probability and mathematical statistics is becoming an indispensable discipline in many branches of science and engineering. This is caused by increasing significance of various uncertainties affecting performance of complex technological systems. Fundamental concepts and procedures used in analysis of these systems are often based on the theory of probability and mathematical statistics. The book sets out fundamental principles of the probability theory, supplemented by theoretical models of random variables, evaluation of experimental data, sampling theory, distribution updating and tests of statistical hypotheses. Basic concepts of Bayesian approach to probability and two-dimensional random variables, are also covered. Examples of reliability analysis and risk assessment of technological systems are used throughout the book to illustrate basic theoretical concepts and their applications. The primary audience for the book includes undergraduate and graduate students of science and engineering, scientific workers and engineers and specialists in the field of reliability analysis and risk assessment. Except basic knowledge of undergraduate mathematics no special prerequisite is required.
Author : William C. Navidi
Publisher : McGraw-Hill Science, Engineering & Mathematics
Page : 0 pages
File Size : 54,8 Mb
Release : 2004-12
Category : Bootstrap (Statistics)
ISBN : 0073107670
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.
Author : David M. Levine,Patricia P. Ramsey,Robert K. Smidt
Publisher : Pearson
Page : 746 pages
File Size : 46,5 Mb
Release : 2001
Category : Electronic spreadsheets
ISBN : UCSD:31822033772393
For courses in Probability and Statistics. This applied text for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important to students in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software (Microsoft Excel and Minitab) as well as in-depth coverage of quality and experimental design complete this treatment of statistics.
Author : Robert V. Hogg,Johannes Ledolter
Publisher : Prentice Hall
Page : 504 pages
File Size : 42,6 Mb
Release : 1992
Category : Computers
ISBN : UOM:39015025277420
"Written by two of the leading figures in statistics, this highly regarded volume thoroughly addresses the full range of required topics." provides early discussed fundamental concepts such as variability, graphical representation of data, and randomization and blocking in design of experiments. provides a thorough introduction to descriptive statistics, including the importance of understanding variability, representation of data, exploratory data analysis, and time-sequence plots. explores principles of probability, probability distributions, and sampling distribution theory. discusses regression, design of experiments and their analysis, including factorial and fractional factorial designs.
Author : Jiju Antony
Publisher : Elsevier
Page : 296 pages
File Size : 42,5 Mb
Release : 2023-06-02
Category : Technology & Engineering
ISBN : 9780443151743
This third edition of Design of Experiments for Engineers and Scientists adds to the tried and trusted tools that were successful in so many engineering organizations with new coverage of design of experiments (DoE) in the service sector. Case studies are updated throughout, and new ones are added on dentistry, higher education, and utilities. Although many books have been written on DoE for statisticians, this book overcomes the challenges a wider audience faces in using statistics by using easy-to-read graphical tools. Readers will find the concepts in this book both familiar and easy to understand, and users will soon be able to apply them in their work or research. This classic book is essential reading for engineers and scientists from all disciplines tackling all kinds of product and process quality problems and will be an ideal resource for students of this topic. Written in nonstatistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem-solving methodology New edition includes two new chapters on DoE for services as well as case studies illustrating its wider application in the service industry
Author : Pierre Moulin,Venugopal V. Veeravalli
Publisher : Cambridge University Press
Page : 423 pages
File Size : 50,6 Mb
Release : 2019
Category : Mathematics
ISBN : 9781107185920
A mathematically accessible textbook introducing all the tools needed to address modern inference problems in engineering and data science.