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Stats

Stats
  • Author : David E. Bock,Paul F. Velleman,Richard D. De Veaux
  • Publisher :Unknown
  • Release Date :2015-04-23
  • Total pages :864
  • ISBN : 0134243927
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Summary : This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Clear, accessible, and teachable, Stats: Modeling the World leads with practical data analysis and graphics to engage students and get them thinking statistically from the start. Through updated, relevant examples and data—and the authors’ signature Think, Show, and Tell problem-solving method—students learn what we can find in data, why we find it interesting, and how to report it to others. The new Fourth Edition is even more engaging than previous editions, builds on the innovative features that have made the first three editions so popular, and includes revisions designed to make it even easier for students to put the concepts of statistics together in a coherent whole.

Stats

Stats
  • Author : David E. Bock,Paul F. Velleman,Richard D. De Veaux
  • Publisher :Unknown
  • Release Date :2007-03-30
  • Total pages :680
  • ISBN : 9780131731318
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Summary :

STATS Modeling the World

STATS Modeling the World
  • Author : Bock,Velleman,De Veaux
  • Publisher :Unknown
  • Release Date :2006-01-01
  • Total pages :816
  • ISBN : 9780131876248
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Summary :

Stats

Stats
  • Author : David Bock,Richard D. De Veaux,Paul Velleman
  • Publisher :Unknown
  • Release Date :2003-12-01
  • Total pages :229
  • ISBN : 9780321267436
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Summary : The son of a brewer, Thomas Cromwell rose from obscurity to become the confidant of the King and one of the most influ ential men in British history. Cromwell drafted the law that allowed Henry VIII to divorce his first wife and marry Anne Boleyn, setting into motion the brutal Pro testant Reformation. Over the course of his career, Cromwell amassed a fortune through bribery and theft, and created many enemies along the way. His fall was spectacular—beheaded out side the Tower of London, his boiled head was placed on a spike above the London Bridge. Rich in incident and colorful detail, this is narrative history at its finest.

Stats

Stats
  • Author : Bock,David E. Bock,Paul F. Velleman,Richard D. De Veaux
  • Publisher :Unknown
  • Release Date :2006-02-01
  • Total pages :816
  • ISBN : 9780131963221
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Summary :

Preparing for the Statistics AP Exam

Preparing for the Statistics AP Exam
  • Author : Anne Carroll
  • Publisher :Unknown
  • Release Date :2003-11-01
  • Total pages :285
  • ISBN : 9780321173447
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Summary :

Graphing Calculator Manual for Stats

Graphing Calculator Manual for Stats
  • Author : Patricia Humphrey,David E. Bock,John Diehl,Paul F. Velleman,Richard D. De Veaux
  • Publisher :Unknown
  • Release Date :2009-03-30
  • Total pages :121
  • ISBN : 9780321570949
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Summary : Organized to follow the sequence of topics in the text, this manual is an easy-to-follow, step-by-step guide on how to use the TI-83/84 Plus and TI-89 graphing calculators. It provides worked-out examples to help students fully understand and use their graphing calculator

Stats MyLab Business Statistics Access Code

Stats MyLab Business Statistics Access Code
  • Author : David E Bock,Paul F Velleman,Floyd Bullard,Richard D de Veaux
  • Publisher :Unknown
  • Release Date :2018-05-12
  • Total pages :229
  • ISBN : 9780134782911
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Summary : MyLab Statistics Standalone Access Card to accompany Bock/Velleman/DeVeaux/Bullard, Stats: Modeling the World, 5e This item is an access card for MyLab(TM) Statistics. This physical access card includes an access code for your MyLab Statistics course. In order to access the online course you will also need a Course ID, provided by your instructor. This title-specific access card provides access to the Bock/Velleman/DeVeaux/Bullard, Stats: Modeling the World, 5e accompanying MyLab course ONLY. 0134782917 / 9780134782911 MYLAB STATISTICS WITH PEARSON ETEXT -- STANDALONE ACCESS CARD -- FOR STATS: MODELING THE WORLD, 5/e MyLab Statistics is the world's leading online tutorial, and assessment program designed to help you learn and succeed in your mathematics course. MyLab Statistics online courses are created to accompany one of Pearson's best-selling math textbooks. Every MyLab Statistics course includes a complete, interactive eText. Learn more about MyLab Statistics. ALERT: Before you purchase, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. Used or rental books If you rent or purchase a used book with an access code, the access code may have been redeemed previously and you may have to purchase a new access code. Access codes Access codes that are purchased from sellers other than Pearson carry a higher risk of being either the wrong ISBN or a previously redeemed code. Check with the seller prior to purchase.

Exam Prep for: Stats Modeling the World

Exam Prep for: Stats Modeling the World
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :229
  • ISBN : 09876543XX
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Summary :

Exam Prep for: Stats; Modeling the World

Exam Prep for: Stats; Modeling the World
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :229
  • ISBN : 09876543XX
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Summary :

Exam Prep for: Stats Modeling the World Books a la carte ...

Exam Prep for: Stats Modeling the World Books a la carte ...
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :229
  • ISBN : 09876543XX
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Summary :

Exam Prep for: Stats; Modeling the World Nasta Edition ...

Exam Prep for: Stats; Modeling the World Nasta Edition ...
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :229
  • ISBN : 09876543XX
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Summary :

Exam Prep for: Videos on DVD for Stats; Modeling the World

Exam Prep for: Videos on DVD for Stats; Modeling the World
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :229
  • ISBN : 09876543XX
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Summary :

Stats in Your World

Stats in Your World
  • Author : David E. Bock,Thomas J. Mariano,William B. Craine,Paul Velleman,Richard D. De Veaux
  • Publisher :Unknown
  • Release Date :2015-01-01
  • Total pages :600
  • ISBN : 9780321979513
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Summary :

Modeling with Data

Modeling with Data
  • Author : Ben Klemens
  • Publisher :Unknown
  • Release Date :2008-10-06
  • Total pages :472
  • ISBN : 9781400828746
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Summary : Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date. Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.

Exam Prep Flash Cards for Stats: Modeling the World

Exam Prep Flash Cards for Stats: Modeling the World
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :229
  • ISBN : 09876543XX
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Summary :

Bayesian Modeling in Bioinformatics

Bayesian Modeling in Bioinformatics
  • Author : Dipak K. Dey,Samiran Ghosh,Bani K. Mallick
  • Publisher :Unknown
  • Release Date :2010-09-03
  • Total pages :466
  • ISBN : 9781420070187
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Summary : Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene expression and phylogenic analysis. The book explores Bayesian techniques and models for detecting differentially expressed genes, classifying differential gene expression, and identifying biomarkers. It develops novel Bayesian nonparametric approaches for bioinformatics problems, measurement error and survival models for cDNA microarrays, a Bayesian hidden Markov modeling approach for CGH array data, Bayesian approaches for phylogenic analysis, sparsity priors for protein-protein interaction predictions, and Bayesian networks for gene expression data. The text also describes applications of mode-oriented stochastic search algorithms, in vitro to in vivo factor profiling, proportional hazards regression using Bayesian kernel machines, and QTL mapping. Focusing on design, statistical inference, and data analysis from a Bayesian perspective, this volume explores statistical challenges in bioinformatics data analysis and modeling and offers solutions to these problems. It encourages readers to draw on the evolving technologies and promote statistical development in this area of bioinformatics.

Moneyball: The Art of Winning an Unfair Game

Moneyball: The Art of Winning an Unfair Game
  • Author : Michael Lewis
  • Publisher :Unknown
  • Release Date :2004-03-17
  • Total pages :320
  • ISBN : 9780393066234
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Summary : "This delightfully written, lesson-laden book deserves a place of its own in the Baseball Hall of Fame." —Forbes Moneyball is a quest for the secret of success in baseball. In a narrative full of fabulous characters and brilliant excursions into the unexpected, Michael Lewis follows the low-budget Oakland A's, visionary general manager Billy Beane, and the strange brotherhood of amateur baseball theorists. They are all in search of new baseball knowledge—insights that will give the little guy who is willing to discard old wisdom the edge over big money.

Domain Modeling Made Functional

Domain Modeling Made Functional
  • Author : Scott Wlaschin
  • Publisher :Unknown
  • Release Date :2018-01-25
  • Total pages :312
  • ISBN : 1680505491
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Summary : You want increased customer satisfaction, faster development cycles, and less wasted work. Domain-driven design (DDD) combined with functional programming is the innovative combo that will get you there. In this pragmatic, down-to-earth guide, you'll see how applying the core principles of functional programming can result in software designs that model real-world requirements both elegantly and concisely - often more so than an object-oriented approach. Practical examples in the open-source F# functional language, and examples from familiar business domains, show you how to apply these techniques to build software that is business-focused, flexible, and high quality. Domain-driven design is a well-established approach to designing software that ensures that domain experts and developers work together effectively to create high-quality software. This book is the first to combine DDD with techniques from statically typed functional programming. This book is perfect for newcomers to DDD or functional programming - all the techniques you need will be introduced and explained. Model a complex domain accurately using the F# type system, creating compilable code that is also readable documentation---ensuring that the code and design never get out of sync. Encode business rules in the design so that you have "compile-time unit tests," and eliminate many potential bugs by making illegal states unrepresentable. Assemble a series of small, testable functions into a complete use case, and compose these individual scenarios into a large-scale design. Discover why the combination of functional programming and DDD leads naturally to service-oriented and hexagonal architectures. Finally, create a functional domain model that works with traditional databases, NoSQL, and event stores, and safely expose your domain via a website or API. Solve real problems by focusing on real-world requirements for your software. What You Need: The code in this book is designed to be run interactively on Windows, Mac and Linux.You will need a recent version of F# (4.0 or greater), and the appropriate .NET runtime for your platform.Full installation instructions for all platforms at fsharp.org.

Bayesian Methods for Hackers

Bayesian Methods for Hackers
  • Author : Cameron Davidson-Pilon
  • Publisher :Unknown
  • Release Date :2015-09-30
  • Total pages :256
  • ISBN : 0133902927
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Summary : Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

Introductory Statistics

Introductory Statistics
  • Author : Barbara Illowsky,Susan Dean
  • Publisher :Unknown
  • Release Date :2017-12-19
  • Total pages :906
  • ISBN : 9789888407309
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Summary : Introductory Statistics is designed for the one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. The foundation of this textbook is Collaborative Statistics, by Barbara Illowsky and Susan Dean. Additional topics, examples, and ample opportunities for practice have been added to each chapter. The development choices for this textbook were made with the guidance of many faculty members who are deeply involved in teaching this course. These choices led to innovations in art, terminology, and practical applications, all with a goal of increasing relevance and accessibility for students. We strove to make the discipline meaningful, so that students can draw from it a working knowledge that will enrich their future studies and help them make sense of the world around them. Coverage and Scope Chapter 1 Sampling and Data Chapter 2 Descriptive Statistics Chapter 3 Probability Topics Chapter 4 Discrete Random Variables Chapter 5 Continuous Random Variables Chapter 6 The Normal Distribution Chapter 7 The Central Limit Theorem Chapter 8 Confidence Intervals Chapter 9 Hypothesis Testing with One Sample Chapter 10 Hypothesis Testing with Two Samples Chapter 11 The Chi-Square Distribution Chapter 12 Linear Regression and Correlation Chapter 13 F Distribution and One-Way ANOVA