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Book
Analyse statistique de données avec Student Systat : version Windows
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ISBN: 9782841800032 2841800032 Year: 1995 Publisher: Paris International Tomson publishing France

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Data analysis with JMP IN 4
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ISBN: 9780534373955 053437395X Year: 2000 Publisher: Pacific Grove: Duxbury,

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Data analysis with Microsoft® Excel
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ISBN: 0534362788 Year: 2000 Publisher: Pacific Grove, Calif. Duxbury/Thomson Learning

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Programming


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Data analysis with Microsoft Excel : updated for Office 2007.
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ISBN: 0495831492 9780495831495 Year: 2010 Publisher: Boston Brooks/Cole

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Data analysis with Microsoft Excel
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ISBN: 0534529291 Year: 1998 Publisher: Pacific Grove Brooks/Cole

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Book
Modern Mathematical Statistics with Applications
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ISSN: 1431875X ISBN: 1461403901 146140391X Year: 2012 Publisher: New York, NY : Springer New York : Imprint: Springer,

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Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without much attention paid to how statistics is actually used.. In contrast, Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data. The main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research. It begins with a chapter on descriptive statistics that immediately exposes the reader to real data. The next six chapters develop the probability material that bridges the gap between descriptive and inferential statistics. Point estimation, inferences based on statistical intervals, and hypothesis testing are then introduced in the next three chapters. The remainder of the book explores the use of this methodology in a variety of more complex settings. This edition includes a plethora of new exercises, a number of which are similar to what would be encountered on the actuarial exams that cover probability and statistics. Representative applications include investigating whether the average tip percentage in a particular restaurant exceeds the standard 15%, considering whether the flavor and aroma of Champagne are affected by bottle temperature or type of pour, modeling the relationship between college graduation rate and average SAT score, and assessing the likelihood of O-ring failure in space shuttle launches as related to launch temperature. Other features include: - An extensive range of applications that will appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and business, economics, and quantitative social science students. - Nearly 1,500 exercises to help students master the material and better understand sophisticated concepts and arguments. - An emphasis on the importance of statistical software, including output from the statistical software packages Minitab, R, and SAS.


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Modern mathematical statistics with applications
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ISBN: 0495118605 9780495118602 Year: 2007 Publisher: Belmont (Calif.) : Thomson, Brooks/Cole,

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Digital
Modern Mathematical Statistics with Applications
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ISBN: 9781461403913 Year: 2012 Publisher: New York, NY Springer New York

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Book
Modern Mathematical Statistics with Applications
Authors: --- ---
ISBN: 9781461403913 Year: 2012 Publisher: New York, NY Springer New York

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Abstract

Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without much attention paid to how statistics is actually used.. In contrast, Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data.   The main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research.  It begins with a chapter on descriptive statistics that immediately exposes the reader to real data.  The next six chapters develop the probability material that bridges the gap between descriptive and inferential statistics.  Point estimation, inferences based on statistical intervals, and hypothesis testing are then introduced in the next three chapters.  The remainder of the book explores the use of this methodology in a variety of more complex settings.   This edition includes a plethora of new exercises, a number of which are similar to what would be encountered on the actuarial exams that cover probability and statistics. Representative applications include investigating whether the average tip percentage in a particular restaurant exceeds the standard 15%, considering whether the flavor and aroma of Champagne are affected by bottle temperature or type of pour, modeling the relationship between college graduation rate and average SAT score, and assessing the likelihood of O-ring failure in space shuttle launches as related to launch temperature.   Other features include: - An extensive range of applications that will appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and business, economics, and quantitative social science students. - Nearly 1,500 exercises to help students master the material and better understand sophisticated concepts and arguments. - An emphasis on the importance of statistical software, including output from the statistical software packages Minitab, R, and SAS.


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Modern Mathematical Statistics with Applications
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ISBN: 9783030551568 9783030551575 9783030551582 9783030551551 Year: 2021 Publisher: Cham Springer International Publishing

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This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. Here is a small but representative selection of scenarios for our examples and exercises based on information in recent articles: Use of the "Big Mac index" by the publication The Economist as a humorous way to compare product costs across nations Visualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettes Describing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical stapler Estimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmet Investigating the relationship between body mass index and foot load while running The main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings. This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions. There are more than 1300 exercises in the book, ranging from very straightforward to reasonably challenging. Many sections have been rewritten with the goal of streamlining and providing a more accessible exposition. Output from the most common statistical software packages is included wherever appropriate (a feature absent from virtually all other mathematical statistics textbooks). The authors hope that their enthusiasm for the theory and applicability of statistics to real world problems will encourage students to pursue more training in the discipline.

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