Book picks similar to
Bayesian Statistics for Beginners: A Step-By-Step Approach by Therese M Donovan
mathematics
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The Old Farmer's Almanac 2016
Old Farmer's Almanac - 2015
Thomas, and readers’ expectations. This edition is packed with wit, wisdom, tips, advice, facts, fun, and recipes, including: • traditionally 80 percent–accurate weather forecasts • how to make sausages at home • “creatures from hell” • grow your own beer (ingredients) • time- and money-saving tips • unmasked mysteries of plant seed dispersal • bale, key, and concrete block gardens • quirky origins of American horse breeds • history, lore, and more about birthstones Plus, Moon phases and other celestial sightings, tides, gardening tables, best days to do things, and more. Added value this year: • 96 full-color pages • full-color winter and summer weather maps • updated Reference section Often imitated, but never equaled. Accept no substitutes!
CliffsNotes Math Review for Standardized Tests
Jerry Bobrow - 2010
Your guide to a higher math score on standardized tests*SATACT(R)ASVABGMAT(R)GRE(R)CBEST(R)PRAXIS I(R)GED(R) And More!Why CliffsNotes?Go with the name you know and trustGet the information you need-fast!About the Contents:IntroductionHow to use this bookOverview of the examsPart I: Basic Skills ReviewArithmetic and Data AnalysisAlgebraPart II: Strategies and PracticeMathematical AbilityQuantitative ComparisonData SufficiencyEach section includes a diagnostic test, explanations of rules, concepts withexamples, practice problems with complete explanations, a review test, and aglossary!Test-Prep Essentials from the Experts at CliffsNotes(R)For more test-prep help, visit CliffsNotes.com(R)*SAT is a registered trademark of the College Board, which was not involved inthe production of, and does not endorse, this product.
The Maudsley Prescribing Guidelines in Psychiatry
David M. Taylor - 1999
Where do you look for information when transferring a patient from one drug to another? Where do you find a clear overview when dealing with a complex patient (e.g, with co-morbid epilepsy or liver disease or HIV infection)? Where can you seek advice on prescribing psychotropics during pregnancy? "The Maudsley Prescribing Guidelines in Psychiatry"! The leading clinical reference for handling prescribing problems as encountered in daily practice and for formulating prescribing policy.Evidence-based and written by expertsThis book is the essential guide for anyone responsible for prescribing, dispensing or administering drugs for patients with mental health disorders. All the evidence has been reviewed and summarized succinctly by an expert team of psychiatrists and pharmacists.New content and improved formatThis new edition makes greater use of tables and boxes to facilitate quick reference and includes new sections on cytochrome-mediated interactions and psychiatric side effects of non-psychotropic drugs.Clinically relevantChapters address plasma monitoring, schizophrenia, bipolar disorder, depression and anxiety, children and adolescents, substance abuse and special patient groups. Each section has a full reference list. The book covers prescribing drugs outside their licensed indications and their interaction with substances such as alcohol, nicotine and caffeine.Useful for all levels of experienceTrainees will gain important information regarding the rational, safe and effective use of medications for patients with mental illness. Experienced clinicians will find excellent guidance regarding more complex issues that they may not encounter regularly.Why the Maudsley Prescribing Guidelines in Psychiatry?Long recognized as an international trailblazer in mental health care, the Maudsley Hospital earned its reputation for excellence in both in-patient and community care. It is highly regarded for its research, and pioneered the use of clinical neuroscience. You can trust "The Maudsley Prescribing Guidelines in Psychiatry" to be scientifically sound and clinically effective.
Odessa Dreams (Kindle Single)
Shaun Walker - 2014
The men spend a week in the port city of Odessa, hoping to find true love and a Ukrainian bride to bring home. The country has a huge dating and marriage industry, but it quickly becomes apparent that all is not what it seems. Walker uncovers scams and disappointments, wounded hearts and broken lives as he journeys to the very bottom of Odessa’s sinister marriage industry. There are many twists and turns to the tale that are as shocking as they are unexpected. Odessa Dreams is by turns hilariously funny, poignantly tragic and deeply disturbing. It is a roller coaster journey that will leave the reader feeling uncomfortable for quite some time. Shaun Walker is Moscow Correspondent for The Guardian, and previously for The Independent. He studied Russian History at Oxford University and has lived in Moscow for a decade.
Introduction to Physical Metallurgy
Sidney H. Avner - 1974
The main ideas and applications of the metallurgy are provided in this book.
Bayesian Data Analysis
Andrew Gelman - 1995
Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.
Proofs and Refutations: The Logic of Mathematical Discovery
Imre Lakatos - 1976
Much of the book takes the form of a discussion between a teacher and his students. They propose various solutions to some mathematical problems and investigate the strengths and weaknesses of these solutions. Their discussion (which mirrors certain real developments in the history of mathematics) raises some philosophical problems and some problems about the nature of mathematical discovery or creativity. Imre Lakatos is concerned throughout to combat the classical picture of mathematical development as a steady accumulation of established truths. He shows that mathematics grows instead through a richer, more dramatic process of the successive improvement of creative hypotheses by attempts to 'prove' them and by criticism of these attempts: the logic of proofs and refutations.
Data Science from Scratch: First Principles with Python
Joel Grus - 2015
In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.
If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.
Get a crash course in Python
Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science
Collect, explore, clean, munge, and manipulate data
Dive into the fundamentals of machine learning
Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering
Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
Data Science for Business: What you need to know about data mining and data-analytic thinking
Foster Provost - 2013
This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates
Re:cyclists: 200 Years on Two Wheels
Michael Hutchinson - 2017
The calls to ban it were more or less instant.Re:cyclists is the tale of what happened next, of how we have spent two centuries wheeling our way about town and country on bikes--or on two-wheeled things that vaguely resembled what we now call bikes. Michael Hutchinson picks his way through those 200 years, discovering how cycling became a kinky vaudeville act for Parisians, how it became an American business empire, and how it went on to find a unique home in the British Isles. He considers the penny-farthing riders exploring the abandoned and lonely coaching roads during the railway era, and the Victorian high-society cyclists of the 1890s bicycle craze--a time when no aristocratic house party was without bicycles and when the Prince of Wales used to give himself an illicit thrill on a weekday afternoon by watching the women's riding-school in the Royal Albert Hall.Re:cyclists looks at how cycling became the sport, the pastime and the social life of millions of ordinary people, how it grew and how it suffered through the 1960s and '70s, and how at the dawn of the twenty-first century it rose again, much changed but still ultimately just someone careering along on two wheels.
The Killing Zone: How & Why Pilots Die
Paul A. Craig - 2000
Presents the statistics of how many pilots will die in the zone within a year; calls attention to the eight top pilot killers (such as "VFR into IFR," "Takeoff and Climb"); and maps strategies for avoiding, diverting, correcting, and managing the dangers. Includes a Pilot Personality Self-Assessment Exercise that identifies pilot "types" and how each type can best react to survive the killing zone.
Mostly Harmless Econometrics: An Empiricist's Companion
Joshua D. Angrist - 2008
In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications
Molecular Biotechnology: Principles & Applications of Recombinant DNA
Bernard R. Glick - 1994
The latest edition offers greatly expanded coverage of directed mutagenesis and protein engineering, therapeutic agents, and genetic engineering of plants. Updated chapters reflect recent developments in biotechnology and the societal issues related to it, such as cloning, gene therapy, and patenting and releasing genetically engineered organisms. Over 480 figures, including 200 that are new in this edition, illustrate all key concepts. "Milestones" summarize important research papers in the history of biotechnology and their effects on the field. As in previous editions, the authors clearly explain all concepts and techniques to provide maximum understanding of the subject, avoiding confusing scientific jargon and excessive detail wherever possible. Each chapter concludes with a summary, references, and review questions. Ideally suited as a text for third- and fourth-year undergraduates as well as graduate students, this book is also an excellent reference for health professionals, scientists, engineers, or attorneys interested in biotechnology.
Bayes' Rule: A Tutorial Introduction to Bayesian Analysis
James V. Stone - 2013
Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, intuitive visual representations of real-world examples are used to show how Bayes' rule is actually a form of commonsense reasoning. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to gain an intuitive understanding of Bayesian analysis. As an aid to understanding, online computer code (in MatLab, Python and R) reproduces key numerical results and diagrams.Stone's book is renowned for its visually engaging style of presentation, which stems from teaching Bayes' rule to psychology students for over 10 years as a university lecturer.