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| tilman davies: Book of R Tilman Davies M., 2016 |
| tilman davies: The Art of R Programming Norman Matloff, 2011-10-11 R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly. The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro. Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: –Create artful graphs to visualize complex data sets and functions –Write more efficient code using parallel R and vectorization –Interface R with C/C++ and Python for increased speed or functionality –Find new R packages for text analysis, image manipulation, and more –Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing. |
| tilman davies: Introductory Statistics with R Peter Dalgaard, 2006-04-06 This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis. |
| tilman davies: The Book of R, 2nd Edition Tilman M. Davies, 2025-09-23 Produce statistical summaries, visualizations of your data, and more with the new edition of this beginner-friendly guide to R programming. Even if you have no programming experience and little more than a grounding in basic math, The Book of R, 2nd Edition will teach you everything you need to know for using R effectively in statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data, performing statistical tests, and modeling. You’ll also learn how to create impressive data visualizations with R’s graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Over 30 of hands-on exercises (with downloadable solutions) take you from theory to practice, as you explore: The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R How to access R’s thousands of functions, libraries, and data sets How to draw valid and useful conclusions from your data How to create publication-quality graphics of your results The second edition has been revised and updated from start to finish, with new content that expands the book’s coverage of statistical operations, data plots, date-time-objects, and more — including dozens of fresh exercises to strengthen your skills. Combining detailed explanations with real-world examples, The Book of R is your doorway into the wide world of data analysis. |
| tilman davies: Statistics Michael J. Crawley, 2005-05-06 Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http://www.imperial.ac.uk/bio/research/crawley/statistics Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R. |
| tilman davies: R in Action, Third Edition Robert Kabacoff, 2022-05-03 'R in Action' presents both the R system and the use cases that make it such a compelling package for business developers. The book begins by introducing the R language, and then moves on to various examples illustrating R's features. |
| tilman davies: R for Data Science Hadley Wickham, Garrett Grolemund, 2016-12-12 Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true signals in your dataset Communicate—learn R Markdown for integrating prose, code, and results |
| tilman davies: R For Dummies Andrie de Vries, Joris Meys, 2012-06-06 Master the programming language of choice among statisticians and data analysts worldwide Coming to grips with R can be tough, even for seasoned statisticians and data analysts. Enter R For Dummies, the quick, easy way to master all the R you'll ever need. Requiring no prior programming experience and packed with practical examples, easy, step-by-step exercises, and sample code, this extremely accessible guide is the ideal introduction to R for complete beginners. It also covers many concepts that intermediate-level programmers will find extremely useful. Master your R ABCs ? get up to speed in no time with the basics, from installing and configuring R to writing simple scripts and performing simultaneous calculations on many variables Put data in its place ? get to know your way around lists, data frames, and other R data structures while learning to interact with other programs, such as Microsoft Excel Make data dance to your tune ? learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and much more Visualize it ? learn to use R's powerful data visualization features to create beautiful and informative graphical presentations of your data Get statistical ? find out how to do simple statistical analysis, summarize your variables, and conduct classic statistical tests, such as t-tests Expand and customize R ? get the lowdown on how to find, install, and make the most of add-on packages created by the global R community for a wide variety of purposes Open the book and find: Help downloading, installing, and configuring R Tips for getting data in and out of R Ways to use data frames and lists to organize data How to manipulate and process data Advice on fitting regression models and ANOVA Helpful hints for working with graphics How to code in R What R mailing lists and forums can do for you |
| tilman davies: The Wages of War, 1816-1965 Joel David Singer, Melvin Small, 1972 |
| tilman davies: Geographic Data Science with R Michael C. Wimberly, 2023-05-08 The burgeoning field of data science has provided a wealth of techniques for analysing large and complex geospatial datasets, including descriptive, explanatory, and predictive analytics. However, applying these methods is just one part of the overall process of geographic data science. Other critical steps include screening for suspect data values, handling missing data, harmonizing data from multiple sources, summarizing the data, and visualizing data and analysis results. Although there are many books available on statistical and machine learning methods, few encompass the broader topic of scientific workflows for geospatial data processing and analysis. The purpose of Geographic Data Science with R is to fill this gap by providing a series of tutorials aimed at teaching good practices for using geospatial data to address problems in environmental geography. It is based on the R language and environment, which currently provides the best option for working with diverse spatial and non-spatial data in a single platform. Fundamental techniques for processing and visualizing tabular, vector, and raster data are introduced through a series of practical examples followed by case studies that combine multiple types of data to address more complex problems. The book will have a broad audience. Both students and professionals can use it as a workbook to learn high-level techniques for geospatial data processing and analysis with R. It is also suitable as a textbook. Although not intended to provide a comprehensive introduction to R, it is designed to be accessible to readers who have at least some knowledge of coding but little to no experience with R. Key Features: Focus on developing practical workflows for processing and integrating multiple sources of geospatial data in R Example-based approach that teaches R programming and data science concepts through real-world applications related to climate, land cover and land use, and natural hazards. Consistent use of tidyverse packages for tabular data manipulation and visualization. Strong focus on analysing continuous and categorical raster datasets using the new terra package Organized so that each chapter builds on the topics and techniques covered in the preceding chapters Can be used for self-study or as the textbook for a geospatial science course. |
| tilman davies: R for the Rest of Us David Keyes, 2024-06-25 Learn how to use R for everything from workload automation and creating online reports, to interpreting data, map making, and more. Written by the founder of a very popular online training platform for the R programming language! The R programming language is a remarkably powerful tool for data analysis and visualization, but its steep learning curve can be intimidating for some. If you just want to automate repetitive tasks or visualize your data, without the need for complex math, R for the Rest of Us is for you. Inside you’ll find a crash course in R, a quick tour of the RStudio programming environment, and a collection of real-world applications that you can put to use right away. You’ll learn how to create informative visualizations, streamline report generation, and develop interactive websites—whether you’re a seasoned R user or have never written a line of R code. You’ll also learn how to: • Manipulate, clean, and parse your data with tidyverse packages like dplyr and tidyr to make data science operations more user-friendly • Create stunning and customized plots, graphs, and charts with ggplot2 to effectively communicate your data insights • Import geospatial data and write code to produce visually appealing maps automatically • Generate dynamic reports, presentations, and interactive websites with R Markdown and Quarto that seamlessly integrate code, text, and graphics • Develop custom functions and packages tailored to your specific needs, allowing you to extend R’s functionality and automate complex tasks Unlock a treasure trove of techniques to transform the way you work. With R for the Rest of Us, you’ll discover the power of R to get stuff done. No advanced statistics degree required. |
| tilman davies: Making Risky and Important Decisions Ruth Murray-Webster, David Hillson, 2021-06-11 This book offers a practical insight to leaders who need to make good decisions in risky and important situations. The authors describe a process for making risk-intelligent decisions, explaining complex ideas simply, and mapping a route through the myriad interrelated influences when groups make decisions that matter. The approach puts the decision maker—you—at the center and explains how you can think and act differently to make better decisions more of the time. The book shows how to Determine the appropriate level of risk Make decisions in uncertain and turbulent conditions Understand how risks are perceived to identify them accurately Develop new behaviors to improve decision-making Making Risky and Important Decisions: A Leader’s Guide builds on earlier ground-breaking publications from these two recognized thought leaders. Their first book together, Understanding and Managing Risk Attitude, brought together the language of risk and risk-taking with the language of emotional intelligence and emotional literacy. Managing Group Risk Attitude followed, and focused on decision-making groups, creating new insights and frameworks. Both books are positioned as specialist textbooks, despite their relevance to real-world situations. A Short Guide to Risk Appetite brought together the concepts of risk appetite and risk attitude into one place for the first time, cutting through confusing terminology and confused thinking to create a practical way of understanding how much risk is too much risk. This latest installment from Ruth Murray-Webster and David Hillson takes the breadth of their previous work, adds new insights and thinking, and distills it into a highly usable guide for hard-pressed leaders. |
| tilman davies: Learning R Richard Cotton, 2013 Annotation Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, youll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what youve learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can doUse data types such as vectors, arrays, lists, data frames, and stringsExecute code conditionally or repeatedly with branches and loopsApply R add-on packages, and package your own work for othersLearn how to clean data you import from a variety of sourcesUnderstand data through visualization and summary statisticsUse statistical models to pass quantitative judgments about data and make predictionsLearn what to do when things go wrong while writing data analysis code. |
| tilman davies: R Programming for Beginners Nathan Metzler, 2019-11-22 Master the programming skills you need to turn raw, unfiltered data into deep insights and get ready for a data science and analytics career with this definitive guide to R Programming for Beginners! Do you want to get started learning how to program, but don't know where to begin? Are you interested in moving beyond Excel sheets and learning one of the most powerful programming language used in cutting edge research such as machine learning? If you answered yes to any of these questions, then this book might just be what you need. R can be a royal pain in the neck sometimes. Even seasoned programmers and data analysts still struggle with it. But it doesn't have to be you. In this guide, you're going to learn everything you need to do heavy data wrangling in R, with graded exercises and examples at the end to help you reinforce what you've learned. Here's a preview of what you're going to discover in R Programming for Beginners Step-by-step instructions to help you set up and install the R Environment with photos How to properly Execute R Scripts with your favorite code editor Everything you need to know about the R syntax-statements, blocks, comments, and keywords Steps to help you write your very first R script and begin your programming journey The 6 data types supported by the R programming language How to name variables and assign values to them Steps to help you write well-defined user functions effectively How to control program flow with decision making control structures and loops How to visualize data with R programming ...and lots more! Whether you're completely new to programming and have never written a single line of code before, or you're an intermediate or experienced R programmer looking to brush up on the basics, this book has everything you need to master R completely. Scroll to the top of the page and click the Add to Cart button to get started today! |
| tilman davies: Sustainability and the U.S. EPA National Research Council, Policy and Global Affairs, Science and Technology for Sustainability Program, Committee on Incorporating Sustainability in the U.S. Environmental Protection Agency, 2011-09-08 Sustainability is based on a simple and long-recognized factual premise: Everything that humans require for their survival and well-being depends, directly or indirectly, on the natural environment. The environment provides the air we breathe, the water we drink, and the food we eat. Recognizing the importance of sustainability to its work, the U.S. Environmental Protection Agency (EPA) has been working to create programs and applications in a variety of areas to better incorporate sustainability into decision-making at the agency. To further strengthen the scientific basis for sustainability as it applies to human health and environmental protection, the EPA asked the National Research Council (NRC) to provide a framework for incorporating sustainability into the EPA's principles and decision-making. This framework, Sustainability and the U.S. EPA, provides recommendations for a sustainability approach that both incorporates and goes beyond an approach based on assessing and managing the risks posed by pollutants that has largely shaped environmental policy since the 1980s. Although risk-based methods have led to many successes and remain important tools, the report concludes that they are not adequate to address many of the complex problems that put current and future generations at risk, such as depletion of natural resources, climate change, and loss of biodiversity. Moreover, sophisticated tools are increasingly available to address cross-cutting, complex, and challenging issues that go beyond risk management. The report recommends that EPA formally adopt as its sustainability paradigm the widely used three pillars approach, which means considering the environmental, social, and economic impacts of an action or decision. Health should be expressly included in the social pillar. EPA should also articulate its vision for sustainability and develop a set of sustainability principles that would underlie all agency policies and programs. |
| tilman davies: Hands-On Programming with R Garrett Grolemund, 2014-06-13 Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you’ll learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions, and use all of R’s programming tools. RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You’ll gain valuable programming skills and support your work as a data scientist at the same time. Work hands-on with three practical data analysis projects based on casino games Store, retrieve, and change data values in your computer’s memory Write programs and simulations that outperform those written by typical R users Use R programming tools such as if else statements, for loops, and S3 classes Learn how to write lightning-fast vectorized R code Take advantage of R’s package system and debugging tools Practice and apply R programming concepts as you learn them |
| tilman davies: Getting Started with RStudio John Verzani, 2011-09-23 Annotation Dive into the RStudio Integrated Development Environment for using & programming R, the open source software for statistical computing & graphics. This text provides new & experienced users with an overview of RStudio, as well as hands-on instructions for analyzing data, generating reports & developing R software packages. |
| tilman davies: Metacommunities Marcel Holyoak, Mathew A. Leibold, Robert D. Holt, 2005-10 Takes the hallmarks of metapopulation theory to the next level by considering a group of communities, each of which may contain numerous populations, connected by species interactions within communities and the movement of individuals between communities. This book seeks to understand how communities work in fragmented landscapes. |
| tilman davies: R in Action Robert Kabacoff, 2015-03-03 R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data. R in Action, Second Edition is a language tutorial focused on practical problems. Written by a research methodologist, it takes a direct and modular approach to quickly give readers the information they need to produce useful results. Focusing on realistic data analyses and a comprehensive integration of graphics, it follows the steps that real data analysts use to acquire their data, get it into shape, analyze it, and produce meaningful results that they can provide to clients. Purchase of the print book comes with an offer of a free PDF eBook from Manning. Also available is all code from the book. |
| tilman davies: Microbial Extracellular Polymeric Substances Jost Wingender, 1999-10-20 Microbial extracellular polymeric substances (EPS) are the key components for the aggregation of microorganisms in biofilms, flocs and sludge. They are composed of polysaccharides, proteins, nucleic acids, lipids and other biological macromolecules. EPS provide a highly hydrated gel matrix in which microbial cells can establish stable synergistic consortia. Cohesion and adhesion as well as morphology, structure, biological function and other properties such as mechanical stability, diffusion, sorption and optical properties of microbial aggregates are determined by the EPS matrix. Also, the protection of biofilm organisms against biocides is attributed to the EPS. Their matrix allows phase separation in biofiltration and is also important for the degradation of particulate material which is of great importance for the self purification processes in surface waters and for waste water treatment. In this volume, analysis, characterization, composition, regulation, function and interactions of microbial EPS are covered. |
| tilman davies: Advanced R, Second Edition Hadley Wickham, 2019-05-24 Advanced R helps you understand how R works at a fundamental level. It is designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages who want to understand what makes R different and special. This book will teach you the foundations of R; three fundamental programming paradigms (functional, object-oriented, and metaprogramming); and powerful techniques for debugging and optimising your code. By reading this book, you will learn: The difference between an object and its name, and why the distinction is important The important vector data structures, how they fit together, and how you can pull them apart using subsetting The fine details of functions and environments The condition system, which powers messages, warnings, and errors The powerful functional programming paradigm, which can replace many for loops The three most important OO systems: S3, S4, and R6 The tidy eval toolkit for metaprogramming, which allows you to manipulate code and control evaluation Effective debugging techniques that you can deploy, regardless of how your code is run How to find and remove performance bottlenecks The second edition is a comprehensive update: New foundational chapters: Names and values, Control flow, and Conditions comprehensive coverage of object oriented programming with chapters on S3, S4, R6, and how to choose between them Much deeper coverage of metaprogramming, including the new tidy evaluation framework use of new package like rlang (http://rlang.r-lib.org), which provides a clean interface to low-level operations, and purr (http://purrr.tidyverse.org/) for functional programming Use of color in code chunks and figures Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science. He is also the author of R for Data Science (with Garrett Grolemund), R Packages, and ggplot2: Elegant Graphics for Data Analysis. |
| tilman davies: The Nature of Plant Communities J. Bastow Wilson, Andrew D. Q. Agnew, Stephen H. Roxburgh, 2019-03-21 Provides a comprehensive review of the role of species interactions in the process of plant community assembly. |
| tilman davies: Crime Mapping and Spatial Data Analysis using R Juan Medina Ariza, Reka Solymosi, 2023-04-27 Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis. |
| tilman davies: Statistics for Management and Economics Gerald Keller, Brian Warrack, 2003 Teaches students how to apply statistics to real business problems through the authors' unique three-step approach to problem solving. Students learn to identify, compute and interpret the results in the context of the problem. |
| tilman davies: Annual Report of the State Corporation Commission of Virginia Virginia. State Corporation Commission, 1924 |
| tilman davies: Sensitivity Analysis: Matrix Methods in Demography and Ecology Hal Caswell, 2019-04-02 This open access book shows how to use sensitivity analysis in demography. It presents new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases. Readers will discover results on the sensitivity of statistics of longevity, life disparity, occupancy times, the net reproductive rate, and statistics of Markov chain models in demography. They will also see applications of sensitivity analysis to population growth rates, stable population structures, reproductive value, equilibria under immigration and nonlinearity, and population cycles. Individual stochasticity is a theme throughout, with a focus that goes beyond expected values to include variances in demographic outcomes. The calculations are easily and accurately implemented in matrix-oriented programming languages such as Matlab or R. Sensitivity analysis will help readers create models to predict the effect of future changes, to evaluate policy effects, and to identify possible evolutionary responses to the environment. Complete with many examples of the application, the book will be of interest to researchers and graduate students in human demography and population biology. The material will also appeal to those in mathematical biology and applied mathematics. |
| tilman davies: The Statistical Sleuth Fred L. Ramsey, Daniel W. Schafer, 2002 Prepare for exams and succeed in your statistics course with this comprehensive solutions manual! Featuring worked out-solutions to the problems in THE STATISTICAL SLEUTH: A COURSE IN METHODS OF DATA ANALYSIS, 2nd Edition, this manual shows you how to approach and solve problems using the same step-by-step explanations found in your textbook examples. |
| tilman davies: The Physicist and the Philosopher Jimena Canales, 2016-10-04 The explosive debate that transformed our views about time and scientific truth On April 6, 1922, in Paris, Albert Einstein and Henri Bergson publicly debated the nature of time. Einstein considered Bergson's theory of time to be a soft, psychological notion, irreconcilable with the quantitative realities of physics. Bergson, who gained fame as a philosopher by arguing that time should not be understood exclusively through the lens of science, criticized Einstein's theory of time for being a metaphysics grafted on to science, one that ignored the intuitive aspects of time. The Physicist and the Philosopher tells the remarkable story of how this explosive debate transformed our understanding of time and drove a rift between science and the humanities that persists today. Jimena Canales introduces readers to the revolutionary ideas of Einstein and Bergson, describes how they dramatically collided in Paris, and traces how this clash of worldviews reverberated across the twentieth century. She shows how it provoked responses from figures such as Bertrand Russell and Martin Heidegger, and carried repercussions for American pragmatism, logical positivism, phenomenology, and quantum mechanics. Canales explains how the new technologies of the period—such as wristwatches, radio, and film—helped to shape people’s conceptions of time and further polarized the public debate. She also discusses how Bergson and Einstein, toward the end of their lives, each reflected on his rival’s legacy—Bergson during the Nazi occupation of Paris and Einstein in the context of the first hydrogen bomb explosion. The Physicist and the Philosopher is a magisterial and revealing account that shows how scientific truth was placed on trial in a divided century marked by a new sense of time. |
| tilman davies: The Manga Guide to Regression Analysis Shin Takahashi, Iroha Inoue, Co Ltd Trend, 2016-05-01 Like a lot of people, Miu has had trouble learning regression analysis. But with new motivation—in the form of a handsome but shy customer—and the help of her brilliant café coworker Risa, she’s determined to master it. Follow along with Miu and Risa in The Manga Guide to Regression Analysis as they calculate the effect of temperature on iced tea orders, predict bakery revenues, and work out the probability of cake sales with simple, multiple, and logistic regression analysis. You’ll get a refresher in basic concepts like matrix equations, inverse functions, logarithms, and differentiation before diving into the hard stuff. Learn how to: –Calculate the regression equation –Check the accuracy of your equation with the correlation coefficient –Perform hypothesis tests and analysis of variance, and calculate confidence intervals –Make predictions using odds ratios and prediction intervals –Verify the validity of your analysis with diagnostic checks –Perform chi-squared tests and F-tests to check the goodness of fit Whether you’re learning regression analysis for the first time or have just never managed to get your head around it, The Manga Guide to Regression Analysis makes mastering this tricky technique straightforward and fun. |
| tilman davies: Ecology Charles J. Krebs, 2001 This best-selling majors ecology book continues to present ecology as a series of problems for readers to critically analyze. No other text presents analytical, quantitative, and statistical ecological information in an equally accessible style. Reflecting the way ecologists actually practice, the book emphasizes the role of experiments in testing ecological ideas and discusses many contemporary and controversial problems related to distribution and abundance. Throughout the book, Krebs thoroughly explains the application of mathematical concepts in ecology while reinforcing these concepts with research references, examples, and interesting end-of-chapter review questions. Thoroughly updated with new examples and references, the book now features a new full-color design and is accompanied by an art CD-ROM for instructors. The field package also includes The Ecology Action Guide, a guide that encourages readers to be environmentally responsible citizens, and a subscription to The Ecology Place (www.ecologyplace.com), a web site and CD-ROM that enables users to become virtual field ecologists by performing experiments such as estimating the number of mice on an imaginary island or restoring prairie land in Iowa. For college instructors and students. |
| tilman davies: Modality, Aspect and Negation in Persian Azita H. Taleghani, 2008-06-26 This monograph presents a morpho-syntactic investigation on modality, aspect, and negation by concentrating on Persian, and is designed to contribute to theoretical linguistics and the study of Iranian languages. The analysis is based on the Minimalist program. This research challenges the idea that the syntactic structure maps on the semantic interpretation or vice versa. The discussion presented in this monograph shows that the syntactic structure of Persian modals is uniform no matter if the modals are interpreted as having root or epistemic readings. Although it is claimed that modals are raising constructions in different languages, modals in Persian, which does not have subject-raising constructions, show a different syntactic behavior. Furthermore, the structural analysis of the interaction of Persian modals and negation shows that because of the scope interaction of negation and modals, the syntactic structure of modals with respect to negation mostly corresponds to the semantic interpretation of modals. |
| tilman davies: Synthetic Data and Generative AI Vincent Granville, 2024-01-09 Synthetic Data and Generative AI covers the foundations of machine learning, with modern approaches to solving complex problems and the systematic generation and use of synthetic data. Emphasis is on scalability, automation, testing, optimizing, and interpretability (explainable AI). For instance, regression techniques – including logistic and Lasso – are presented as a single method, without using advanced linear algebra. Confidence regions and prediction intervals are built using parametric bootstrap, without statistical models or probability distributions. Models (including generative models and mixtures) are mostly used to create rich synthetic data to test and benchmark various methods. - Emphasizes numerical stability and performance of algorithms (computational complexity) - Focuses on explainable AI/interpretable machine learning, with heavy use of synthetic data and generative models, a new trend in the field - Includes new, easier construction of confidence regions, without statistics, a simple alternative to the powerful, well-known XGBoost technique - Covers automation of data cleaning, favoring easier solutions when possible - Includes chapters dedicated fully to synthetic data applications: fractal-like terrain generation with the diamond-square algorithm, and synthetic star clusters evolving over time and bound by gravity |
| tilman davies: Negotiating Survival Ashley Jackson, 2021-12-01 Two decades on from 9/11, the Taliban now control more than half of Afghanistan. Few would have foreseen such an outcome, and there is little understanding of how Afghans living in Taliban territory have navigated life under insurgent rule. Based on over 400 interviews with Taliban and civilians, this book tells the story of how civilians have not only bargained with the Taliban for their survival, but also ultimately influenced the course of the war in Afghanistan. While the Taliban have the power of violence on their side, they nonetheless need civilians to comply with their authority. Both strategically and by necessity, civilians have leveraged this reliance on their obedience in order to influence Taliban behaviour. Challenging prevailing beliefs about civilians in wartime, Negotiating Survival presents a new model for understanding how civilian agency can shape the conduct of insurgencies. It also provides timely insights into Taliban strategy and objectives, explaining how the organisation has so nearly triumphed on the battlefield and in peace talks. While Afghanistan's future is deeply unpredictable, there is one certainty: it is as critical as ever to understand the Taliban--and how civilians survive their rule. |
| tilman davies: A History of the Rectangular Survey System C. Albert White, 1983 |
| tilman davies: R for Everyone Jared P. Lander, 2017-06-13 Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes Explore R, RStudio, and R packages Use R for math: variable types, vectors, calling functions, and more Exploit data structures, including data.frames, matrices, and lists Read many different types of data Create attractive, intuitive statistical graphics Write user-defined functions Control program flow with if, ifelse, and complex checks Improve program efficiency with group manipulations Combine and reshape multiple datasets Manipulate strings using R’s facilities and regular expressions Create normal, binomial, and Poisson probability distributions Build linear, generalized linear, and nonlinear models Program basic statistics: mean, standard deviation, and t-tests Train machine learning models Assess the quality of models and variable selection Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods Analyze univariate and multivariate time series data Group data via K-means and hierarchical clustering Prepare reports, slideshows, and web pages with knitr Display interactive data with RMarkdown and htmlwidgets Implement dashboards with Shiny Build reusable R packages with devtools and Rcpp Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available. |
| tilman davies: Dive Into Algorithms Bradford Tuckfield, 2021-01-05 Dive Into Algorithms is a broad introduction to algorithms using the Python Programming Language. Dive Into Algorithms is a wide-ranging, Pythonic tour of many of the world's most interesting algorithms. With little more than a bit of computer programming experience and basic high-school math, you'll explore standard computer science algorithms for searching, sorting, and optimization; human-based algorithms that help us determine how to catch a baseball or eat the right amount at a buffet; and advanced algorithms like ones used in machine learning and artificial intelligence. You'll even explore how ancient Egyptians and Russian peasants used algorithms to multiply numbers, how the ancient Greeks used them to find greatest common divisors, and how Japanese scholars in the age of samurai designed algorithms capable of generating magic squares. You'll explore algorithms that are useful in pure mathematics and learn how mathematical ideas can improve algorithms. You'll learn about an algorithm for generating continued fractions, one for quick calculations of square roots, and another for generating seemingly random sets of numbers. You'll also learn how to: • Use algorithms to debug code, maximize revenue, schedule tasks, and create decision trees • Measure the efficiency and speed of algorithms • Generate Voronoi diagrams for use in various geometric applications • Use algorithms to build a simple chatbot, win at board games, or solve sudoku puzzles • Write code for gradient ascent and descent algorithms that can find the maxima and minima of functions • Use simulated annealing to perform global optimization • Build a decision tree to predict happiness based on a person's characteristics Once you've finished this book you'll understand how to code and implement important algorithms as well as how to measure and optimize their performance, all while learning the nitty-gritty details of today's most powerful algorithms. |
| tilman davies: R Cookbook JD Long, Paul Teetor, 2019-06-21 Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform basic functions Simplify data input and output Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data |
| tilman davies: Biodiversity and Conservation: Causes and consequences of biodiversity loss 1 : development, habitat loss and invasive species Richard J. Ladle, 2009 Although 'biodiversity' is a relatively new coinage, scientists have been studying the subject it describes long before the word's first appearance in the language in the mid-1980s. In 1973, for instance, the UK Systematics Association held a symposium on 'The Changing Flora and Fauna of Britain' which concluded that not enough attention was being paid to the conservation of rarities, a conclusion also reached, said the symposium, at a meeting of the Linnaean Society some forty years earlier. By 1980, the Global 2000 Report to the President published by the US Council on Environmental Quality starkly warned of a diminution of up to one-fifth of all species by the turn of the century, and there is now a growing consensus that the world faces a 'biodiversity crisis' - a potentially catastrophic global loss of genetic, ecosystem, and, most obviously, species diversity. Indeed, especially since the UN Convention on Biological Diversity was promulgated in Rio de Janeiro in 1992, conserving biodiversity has become the principal focus of the global conservation movement. Indeed, the study of the origins, maintenance, and protection of diversity has become perhaps the most vibrant offshoot of ecology and conservation studies. It is increasingly taught and studied in universities - and other research institutions - around the world. Addressing the need for an authoritative reference work to make sense of this rapidly growing subject, and its ever more complex and multidisciplinary corpus of scholarly literature, Biodiversity and Conservation is a new title in the Routledge series, Critical Concepts in the Environment. Edited by Richard Ladle of Oxford University's Centre for the Environment, this new Major Work brings together in five volumes the foundational and the very best cutting-edge scholarship to provide a synoptic view of all the key issues and current debates |
| tilman davies: Understanding ECMAScript 6 Nicholas C. Zakas, 2016-08-16 ECMAScript 6 represents the biggest update to the core of JavaScript in the history of the language. In Understanding ECMAScript 6, expert developer Nicholas C. Zakas provides a complete guide to the object types, syntax, and other exciting changes that ECMAScript 6 brings to JavaScript. Every chapter is packed with example code that works in any JavaScript environment so you’ll be able to see new features in action. You’ll learn: –How ECMAScript 6 class syntax relates to more familiar JavaScript concepts –What makes iterators and generators useful –How arrow functions differ from regular functions –Ways to store data with sets, maps, and more –The power of inheritance –How to improve asynchronous programming with promises –How modules change the way you organize code Whether you’re a web developer or a Node.js developer, you’ll find Understanding ECMAScript 6 indispensable on your journey from ECMAScript 5 to ECMAScript 6. |
| tilman davies: Make Python Talk Mark Liu, 2021-08-24 A project-based book that teaches beginning Python programmers how to build working, useful, and fun voice-controlled applications. This fun, hands-on book will take your basic Python skills to the next level as you build voice-controlled apps to use in your daily life. Starting with a Python refresher and an introduction to speech-recognition/text-to-speech functionalities, you’ll soon ease into more advanced topics, like making your own modules and building working voice-controlled apps. Each chapter scaffolds multiple projects that allow you to see real results from your code at a manageable pace, while end-of-chapter exercises strengthen your understanding of new concepts. You’ll design interactive games, like Connect Four and Tic-Tac-Toe, and create intelligent computer opponents that talk and take commands; you’ll make a real-time language translator, and create voice-activated financial-market apps that track the stocks or cryptocurrencies you are interested in. Finally, you’ll load all of these features into the ultimate virtual personal assistant – a conversational VPA that tells jokes, reads the news, and gives you hands-free control of your email, browser, music player, desktop files, and more. Along the way, you’ll learn how to: ● Build Python modules, implement animations, and integrate live data into an app ● Use web-scraping skills for voice-controlling podcasts, videos, and web searches ● Fine-tune the speech recognition to accept a variety of input ● Associate regular tasks like opening files and accessing the web with speech commands ● Integrate functionality from other programs into a single VPA with computational knowledge engines to answer almost any question Packed with cross-platform code examples to download, practice activities and exercises, and explainer images, you’ll quickly become proficient in Python coding in general and speech recognition/text to speech in particular. |
Mount Cook Village - Wikipedia
Mount Cook Village, officially Aoraki / Mount Cook, [a] is located within New Zealand's Aoraki / Mount Cook National Park at the end of State Highway 80, only 15 kilometres (9.3 mi) [3] …
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Mt. Cook Village Tourism: Tripadvisor has 14,311 reviews of Mt. Cook Village Hotels, Attractions, and Restaurants making it your best Mt. Cook Village resource.
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May 23, 2025 · Mount Cook Village, also known as Aoraki, sits under the highest mountain in the region – Mount Cook, the “Cloud Piercer”. The alpine village is like a fairytale setting: a place …
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Things to Do in Mt. Cook Village, Aoraki Mount Cook National Park (Te Wahipounamu): See Tripadvisor's 14,311 traveller reviews and photos of Mt. Cook Village attractions.
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Jun 26, 2019 · The closest settlement to Mount Cook, and the best base from which to explore the area is Mount Cook Village. It is a dramatic and lovely spot and offers a whole range of things …
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Visit Aoraki/Mount Cook National Park to get a glimpse of Mt Cook, the tallest mountain in New Zealand. See glaciers and snowy peaks set under a star-studded sky.
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Sep 17, 2024 · Mt Cook Village sits in the heart of the Aoraki Mt Cook National Park. While small, the village is the start of many adventures to explore New Zealand’s most extreme and most …
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A guide to Mount Cook Village in New Zealand, one of New Zealand's best Adventure towns, including Mt. Cook Village activities, hiking, Mueller Hut, and more.
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Apr 27, 2023 · At the base of Mt. Cook is Mt. Cook Village. Whether you’re planning on scaling Mt. Cook or simply driving around the South Island and looking for a place to stay while visiting …
Visitor's Guide to Mt Cook - New Zealand Trails
A stunning drive along the shores of the emerald blue Lake Pukaki (which gains it’s magical colour from glacial silt) brings visitors to Mt Cook Village, the gateway to the heart of the …
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