Statistics for the Sciences


Author: Martin Buntinas,Gerald Marlowe Funk
Publisher: Duxbury Press
ISBN: N.A
Category: Mathematics
Page: 535
View: 5391

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If you are majoring in the sciences, this is the statistics textbook for you. STATISTICS FOR THE SCIENCES helps you see the beauty of statistics using calculus, and contains applications directly tied to natural and physical sciences. In STATISTICS FOR THE SCIENCES, the math is at the right level, and the exercises and examples appeal to those majoring in natural and physical sciences.

Probability and Statistics for Engineering and the Sciences


Author: Jay L. Devore
Publisher: Cengage Learning
ISBN: 1305465326
Category: Business & Economics
Page: 768
View: 5118

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Put statistical theories into practice with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9th Edition. Always a favorite with statistics students, this calculus-based text offers a comprehensive introduction to probability and statistics while demonstrating how professionals apply concepts, models, and methodologies in today's engineering and scientific careers. Jay Devore, an award-winning professor and internationally recognized author and statistician, emphasizes authentic problem scenarios in a multitude of examples and exercises, many of which involve real data, to show how statistics makes sense of the world. Mathematical development and derivations are kept to a minimum. The book also includes output, graphics, and screen shots from various statistical software packages to give you a solid perspective of statistics in action. A Student Solutions Manual, which includes worked-out solutions to almost all the odd-numbered exercises in the book, is available. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Statistics for Engineering and the Sciences, Sixth Edition


Author: William M. Mendenhall,Terry L. Sincich
Publisher: CRC Press
ISBN: 1498728871
Category: Mathematics
Page: 1166
View: 365

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Prepare Your Students for Statistical Work in the Real World Statistics for Engineering and the Sciences, Sixth Edition is designed for a two-semester introductory course on statistics for students majoring in engineering or any of the physical sciences. This popular text continues to teach students the basic concepts of data description and statistical inference as well as the statistical methods necessary for real-world applications. Students will understand how to collect and analyze data and think critically about the results. New to the Sixth Edition Many new and updated exercises based on contemporary engineering and scientific-related studies and real data More statistical software printouts and corresponding instructions for use that reflect the latest versions of the SAS, SPSS, and MINITAB software Introduction of the case studies at the beginning of each chapter Streamlined material on all basic sampling concepts, such as random sampling and sample survey designs, which gives students an earlier introduction to key sampling issues New examples on comparing matched pairs versus independent samples, selecting the sample size for a designed experiment, and analyzing a two-factor experiment with quantitative factors New section on using regression residuals to check the assumptions required in a simple linear regression analysis The first several chapters of the book identify the objectives of statistics, explain how to describe data, and present the basic concepts of probability. The text then introduces the two methods for making inferences about population parameters: estimation with confidence intervals and hypothesis testing. The remaining chapters extend these concepts to cover other topics useful in analyzing engineering and scientific data, including the analysis of categorical data, regression analysis, model building, analysis of variance for designed experiments, nonparametric statistics, statistical quality control, and product and system reliability.

Statistics for the Social Sciences


Author: R. Mark Sirkin
Publisher: SAGE
ISBN: 9781412905466
Category: Mathematics
Page: 610
View: 9430

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Popular in previous editions, this Third Edition continues to help build students' confidence and ability in doing statistical analysis by slowly moving from concepts that require little computational work to those that require more. Author R. Mark Sirkin once again demonstrates how statistics can be used so that students come to appreciate their usefulness rather than fear them. Statistics for the Social Sciences emphasizes the analysis and interpretation of data to give students a feel for how data interpretation is related to the methods by which the information was obtained.

Statistics for Engineering and the Sciences, Sixth Edition Student Solutions Manual


Author: William M. Mendenhall,Terry L. Sincich,Nancy S. Boudreau
Publisher: CRC Press
ISBN: 1498731856
Category: Mathematics
Page: 458
View: 4817

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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.

Statistics for the Behavioral Sciences


Author: Susan A. Nolan,Thomas Heinzen
Publisher: Macmillan
ISBN: 142923265X
Category: Psychology
Page: 736
View: 2217

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Nolan and Heinzen's uniquely effective introduction to statistics captivates students with its real-world storytelling and examples, its highly visual approach to teaching statistics, its accessible treatment of mathematical topics, and its helpful, step-by-step worked examples. The new edition focuses on enhancing those signature strengths while adding powerful new tools to the book's media offerings.

Student Solutions Manual for Probability and Statistics for Engineering and the Sciences, Fourth Edition


Author: Jay L. Devore,Elizabeth M. Eltinge
Publisher: Wadsworth Publishing Company
ISBN: 9780534242657
Category: Mathematical statistics
Page: 183
View: 5120

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This text emphasizes models, methodology, and applications rather than rigorous mathematical development and theory. It uses real data in both exercise sets and examples.

Statistics for Physical Sciences

An Introduction
Author: Brian Martin
Publisher: Academic Press
ISBN: 0123877601
Category: Mathematics
Page: 302
View: 5258

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"Statistics in physical science is principally concerned with the analysis of numerical data, so in Chapter 1 there is a review of what is meant by an experiment, and how the data that it produces are displayed and characterized by a few simple numbers"--

Easy Statistics for Food Science with R


Author: Abbas F. M. Alkarkhi,Wasin A. A. Alqaraghuli
Publisher: Academic Press
ISBN: 0128142634
Category: Technology & Engineering
Page: 228
View: 2089

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Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs. This book was written to help researchers from different fields to analyze their data and make valid decisions. The development of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods for the analysis and interpretation of data. R statistical software is used throughout the book to analyze the data. Contains numerous step-by-step tutorials help the reader to learn quickly Covers the theory and application of the statistical techniques Shows how to analyze data using R software Provides R scripts for all examples and figures

Statistics for Engineering and the Sciences, Sixth Edition Student Solutions Manual


Author: William M. Mendenhall,Terry L. Sincich,Nancy S. Boudreau
Publisher: CRC Press
ISBN: 1498731996
Category: Mathematics
Page: 458
View: 8366

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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.

Applied Statistics for the Social and Health Sciences


Author: Rachel A. Gordon
Publisher: Routledge
ISBN: 0415875366
Category: Mathematics
Page: 742
View: 7232

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Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish statistical models using contemporary standards. The book targets the social and health science branches such as human development, public health, sociology, psychology, education, and social work in which students bring a wide range of mathematical skills and have a wide range of methodological affinities. For these students, a successful course in statistics will not only offer statistical content but will also help them develop an appreciation for how statistical techniques might answer some of the research questions of interest to them. This book is for use in a two-semester graduate course sequence covering basic univariate and bivariate statistics and regression models for nominal and ordinal outcomes, in addition to covering ordinary least squares regression. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature thorough integration of teaching statistical theory with teaching data processing and analysis teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set. This book is for a two-semester course. For a one-semester course, see http://www.routledge.com/9780415991544/

Bayesian Statistics for the Social Sciences


Author: David Kaplan
Publisher: Guilford Publications
ISBN: 146251667X
Category: Psychology
Page: 318
View: 9791

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Bridging the gap between traditional classical statistics and a Bayesian approach, David Kaplan provides readers with the concepts and practical skills they need to apply Bayesian methodologies to their data analysis problems. Part I addresses the elements of Bayesian inference, including exchangeability, likelihood, prior/posterior distributions, and the Bayesian central limit theorem. Part II covers Bayesian hypothesis testing, model building, and linear regression analysis, carefully explaining the differences between the Bayesian and frequentist approaches. Part III extends Bayesian statistics to multilevel modeling and modeling for continuous and categorical latent variables. Kaplan closes with a discussion of philosophical issues and argues for an "evidence-based" framework for the practice of Bayesian statistics. User-Friendly Features *Includes worked-through, substantive examples, using large-scale educational and social science databases, such as PISA (Program for International Student Assessment) and the LSAY (Longitudinal Study of American Youth). *Utilizes open-source R software programs available on CRAN (such as MCMCpack and rjags); readers do not have to master the R language and can easily adapt the example programs to fit individual needs. *Shows readers how to carefully warrant priors on the basis of empirical data. *Companion website features data and code for the book's examples, plus other resources.

Probability and Statistics for Science and Engineering with Examples in R (First Edition)


Author: Hongshik Ahn
Publisher: Cognella Academic Publishing
ISBN: 9781516513987
Category: Technology & Engineering
Page: 342
View: 5325

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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. Hongshik Ahn holds a Ph.D. in statistics from the University of Wisconsin, Madison. Dr. Ahn is currently a professor in the Department of Applied Mathematics and Statistics at Stony Brook University. He worked at National Center for Toxicological Research, FDA before joining Stony Brook University. Recently he served as the vice president of SUNY Korea. His research interests include tree-structured regression and classification, bioinformatics, generalized linear modeling, and risk assessment. Dr. Ahn has been working on NIH grants on various biostatistical and medical researches. He has been published in three book chapters and over 60 peer-reviewed journals. Dr. Ahn also published a book entitled Mathematical Analysis of Genesis, from Shinil Books.

Probability and Statistics for Engineering and the Sciences


Author: CTI Reviews
Publisher: Cram101 Textbook Reviews
ISBN: 1619057166
Category: Education
Page: 74
View: 6493

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Facts101 is your complete guide to Probability and Statistics for Engineering and the Sciences. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

Think Stats


Author: Allen B. Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1491907371
Category: Computers
Page: 226
View: 5276

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If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts. New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries. Develop an understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data