[PDF] Statistics For Science And Engineering eBook

Author : John J. Kinney
Publisher : Pearson
Page : 0 pages
File Size : 35,28 MB
Release : 2002
Category : Mathematical statistics
ISBN : 9780201437201

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Statistics for Science and Engineering was written for an introductory one or two semester course in probability and statistics for junior or senior level students. It is an introduction to the statistical analysis of data that arise from experiments, sample surveys, or other observational studies. It focuses on topics that are frequently used by scientists and engineers, particularly the topics of regression, design of experiments, and statistical process control. Graphs and Statistics, Random Variables and Probability Distributions, Estimation and Hypothesis Testing, Simple Linear Regression-Summarizing Data with Equations, Multiple Linear Regression, Design of Science and Engineering Experiments, Statistical Process Control For all readers interested in statistics for science and engineering.

Author : William M. Mendenhall
Publisher : CRC Press
Page : 458 pages
File Size : 34,2 MB
Release : 2016-11-17
Category : Mathematics
ISBN : 1498731856

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A companion to Mendenhall and Sincich’s Statistics for Engineering and the Sciences, Sixth Edition, this student resource offers full solutions to all of the odd-numbered exercises.

Author : David W. Scott
Publisher : John Wiley & Sons
Page : 180 pages
File Size : 25,47 MB
Release : 2020-07-13
Category : Mathematics
ISBN : 1119675847

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Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics. The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest. Topics discussed include: • Classical equally likely outcomes • Variety of models of discrete and continuous probability laws • Likelihood function and ratio • Inference • Bayesian statistics With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.

Author : William Cyrus Navidi
Publisher : College Ie Overruns
Page : 582 pages
File Size : 40,38 MB
Release : 2010
Category : Engineering
ISBN : 9780070166974

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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 : Paul H. Kvam
Publisher : John Wiley & Sons
Page : 448 pages
File Size : 30,81 MB
Release : 2007-08-24
Category : Mathematics
ISBN : 9780470168691

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A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.

Author : Peter R. Nelson
Publisher : Academic Press
Page : 528 pages
File Size : 33,33 MB
Release : 2003-08-14
Category : Mathematics
ISBN : 0125154232

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A concise treatment for undergraduate and graduate students who need a guide to statistics that focuses specifically on engineering.

Author : Hongshik Ahn
Publisher :
Page : 0 pages
File Size : 14,11 MB
Release : 2022-12-08
Category : Technology & Engineering
ISBN :

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Probability and Statistics for Science and Engineering with Examples in R teaches students how to use R software to obtain summary statistics, calculate probabilities and quantiles, find confidence intervals, and conduct statistical testing. The first chapter introduces methods for describing statistics. Over the course of the subsequent eight chapters students will learn about probability, discrete and continuous distributions, multiple random variables, point estimation and testing, and inferences based on one and two samples. The book features a comprehensive table for each type of test to help students choose appropriate statistical tests and confidence intervals. Based on years of classroom experience and extensively class-tested, Probability and Statistics for Science and Engineering with Examples in R is designed for one-semester courses in probability and statistics, and specifically for students in the natural sciences or engineering. The material is also suitable for business and economics students who have studied calculus.

Author : Steven L. Brunton
Publisher : Cambridge University Press
Page : 615 pages
File Size : 22,2 MB
Release : 2022-05-05
Category : Computers
ISBN : 1009098489

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A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.