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STATISTICS: LEARNING FROM DATA, Second Edition, helps you learn to think like a statistician. It pays particular attention to areas that students often struggle with -- probability, hypothesis testing, and selecting an appropriate method of analysis. Supported by learning objectives, real-data examples and exercises, and technology notes, this book helps you to develop conceptual understanding, mechanical proficiency, and the ability to put knowledge into practice.

Fulfilling the need for a practical user’s guide, Statistics in MATLAB: A Primer provides an accessible introduction to the latest version of MATLAB® and its extensive functionality for statistics. Assuming a basic knowledge of statistics and probability as well as a fundamental understanding of linear algebra concepts, this book: Covers capabilities in the main MATLAB package, the Statistics Toolbox, and the student version of MATLAB Presents examples of how MATLAB can be used to analyze data Offers access to a companion website with data sets and additional examples Contains figures and visual aids to assist in application of the software Explains how to determine what method should be used for analysis Statistics in MATLAB: A Primer is an ideal reference for undergraduate and graduate students in engineering, mathematics, statistics, economics, biostatistics, and computer science. It is also appropriate for a diverse professional market, making it a valuable addition to the libraries of researchers in statistics, computer science, data mining, machine learning, image analysis, signal processing, and engineering.

NOTE - This is a stand-alone book. Intended primarily for undergraduate courses in business statistics, this text also provides practical content to current and aspiring industry professionals. Reducing the emphasis on doing computations, this practical text thoroughly integrates Microsoft Excel as a tool for analysis and presents statistical concepts in the context of the functional areas of business.

This book is written for the Six Sigma Black Belt who needs an understanding of many statistical methods but does not use all of these methods every day. It is intended to be used as a quick reference, providing basic details, step-by-step instructions, and Minitab statistical software instructions. Six Sigma Black Belts typically use a statistical program such as Minitab to perform calculations, but an understanding of the underlying statistics is still needed. Anybody can type data into a program; a Black Belt must be capable of understanding which hypothesis test is appropriate for a given use, as well as the assumptions that must be met to correctly perform the hypothesis test. The methods presented here are laid out according to the Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) phases in which they are typically used. However, these methods can also be applied outside of a Six Sigma project, such as when one simply needs to determine whether there is a difference in the means of two processes producing the same parts. A Six Sigma Black Belt using Statistics for Six Sigma Black Belts will be able to quickly zero in on appropriate methods and follow the examples to reach the correct statistical conclusions.

Special National University Edition for Biostats Class.

How to get to the truth with statistics

Statistics for Engineers and Scientists stands out for its crystal clear presentation of applied statistics. The book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work. This edition 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.McGraw-Hill Education's Connect is also available. Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need, when they need it, how they need it, so that class time is more effective. Connect allows the professor to assign homework, quizzes, and tests easily and automatically grades and records the scores of the student's work. Problems are randomized to prevent sharing of answers an may also have a "multi-step solution" which helps move the students' learning along if they experience difficulty.

This book presents statistical concepts and techniques in simple, everyday language to help readers gain a better understanding of how they work and how to interpret them correctly. Each self-contained chapter features a description of the statistic including how it is used and the information it provides, how to calculate the formula, the strengths and weaknesses of each technique, the conditions needed for its use, and an example that uses and interprets the statistic. A glossary of terms and symbols is also included along with an Interactive CD with PowerPoint presentations and problems and solutions for each chapter. This brief paperback is an ideal supplement for statistics, research methods, or any course that uses statistics, or as a handy reference tool to refresh one's memory about key concepts. The actual research examples are from a variety of fields, including psychology and education.

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A fresh, less formal treatment of classical theoretical probability and statistics is written at an accessible level, with a Bayesian flavor and an emphasis on data and interesting applications. It is designed for the two-term calculus-based mathematical statistics course at the junior level.

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Written by a quantitative psychologist, this textbook explains complex statistics in accessible language to undergraduates in all branches of the social sciences. Built around the central framework of the General Linear Model (GLM), Statistics for the Social Sciences teaches students how different statistical methods are interrelated to one another. With the GLM as a basis, students with varying levels of background are better equipped to interpret statistics and learn more advanced methods in their later courses. Russell T. Warne makes statistics relevant to students' varying majors by using fascinating real-life examples from the social sciences. Students who use this book will benefit from clear explanations, warnings against common erroneous beliefs about statistics, and the latest developments in the philosophy, reporting and practice of statistics in the social sciences. The textbook is packed with helpful pedagogical features including learning goals, guided practice and reflection questions.

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This is a statistics textbook to be used in an introductory statistics class. This book uses technology to calculate probabilities. The approach to this textbook is to ask people to interpret statistics and think statistically.

Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on, example-based approach that teaches students the basics of R and microarray technology as well as how to choose and apply the proper data analysis tool to specific problems. New to the Second EditionCompletely updated and double the size of its predecessor, this timely second edition replaces the commercial software with the open source R and Bioconductor environments. Fourteen new chapters cover such topics as the basic mechanisms of the cell, reliability and reproducibility issues in DNA microarrays, basic statistics and linear models in R, experiment design, multiple comparisons, quality control, data pre-processing and normalization, Gene Ontology analysis, pathway analysis, and machine learning techniques. Methods are illustrated with toy examples and real data and the R code for all routines is available on an accompanying CD-ROM. With all the necessary prerequisites included, this best-selling book guides students from very basic notions to advanced analysis techniques in R and Bioconductor. The first half of the text presents an overview of microarrays and the statistical elements that form the building blocks of any data analysis. The second half introduces the techniques most commonly used in the analysis of microarray data.

Statistics is a subject that many veterinary and other animal science students approach with foreboding, but it is essential for them to grasp the basics in order to understand their subject and play a contributive part in it. This is true whether they be practitioners, research scientists, diagnosticians, or run commercial pathology services, work in research and development of veterinary drugs, or simply care for healthy animals in performance and production. The increasing need to keep up with the literature and to evaluate the competitive promotions for animal systems and health products requires that students have a sound foundation in biological statistics applied to animal care. The emergence of new diseases requires that risk factors associated with them are carefully evaluated. This introductory book will lead the reader through the basics and form a bridge to more complicated statistical procedures found in advanced texts. Written in a non-mathematical way, it contains numerous worked examples helping the reader to develop understanding of the procedures rather than simply the mechanical abilities to perform them.

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Statistics, 2nd Edition teaches statistics with a modern, data-analytic approach that uses graphing calculators and statistical software. It allows more emphasis to be put on statistical concepts and data analysis rather than following recipes for calculations. This gives readers a more realistic understanding of both the theoretical and practical applications of statistics, giving them the ability to master the subject.