All students and professors need to write, and many struggle to finish their stalled dissertations, journal articles, book chapters, or grant proposals. Writing is hard work and can be difficult to wedge into a frenetic academic schedule. In this practical, light-hearted, and encouraging book, Paul Silvia explains that writing productively does not require innate skills or special traits but specific tactics and actions. Drawing examples from his own field of psychology, he shows readers how to overcome motivational roadblocks and become prolific without sacrificing evenings, weekends, and vacations. After describing strategies for writing productively, the author gives detailed advice from the trenches on how to write, submit, revise, and resubmit articles, how to improve writing quality, and how to write and publish academic work.

This book chronicles my six years of working towards a Ph.D. in Computer Science at Stanford University from 2006 to 2012. A diverse variety of people can benefit from reading it, including:
undergraduates who might be interested in pursuing a Ph.D.,
current Ph.D. students who are seeking guidance or inspiration,
professors who want to better understand Ph.D. students,
employers who hire and manage people with Ph.D. degrees,
professionals working in any creative or competitive field where self-driven initiative is crucial,
and educated adults (or precocious kids) who are curious about how academic research is produced.

The Research Funding Toolkit provides this knowledge and offers a range of practical techniques to help you succeed in tough research funding competitions. A complex set of factors determine whether research projects win grants. This handbook helps you navigate these issues and identify your personal challenges to research grant success.

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for "wide" data (p bigger than n), including multiple testing and false discovery rates.

To tap into the power of Python's open data science stack—including NumPy, Pandas, Matplotlib, Scikit-learn, and other tools—you first need to understand the syntax, semantics, and patterns of the Python language. This report provides a brief yet comprehensive introduction to Python for engineers, researchers, and data scientists who are already familiar with another programming language.
Author Jake VanderPlas, an interdisciplinary research director at the University of Washington, explains Python’s essential syntax and semantics, built-in data types and structures, function definitions, control flow statements, and more, using Python 3 syntax.
You’ll explore:
- Python syntax basics and running Python code
Basic semantics of Python variables, objects, and operators
- Built-in simple types and data structures
- Control flow statements for executing code blocks conditionally
- Methods for creating and using reusable functions
Iterators, list comprehensions, and generators
- String manipulation and regular expressions
- Python’s standard library and third-party modules
- Python’s core data science tools
- Recommended resources to help you learn more

'A Byte of Python' is a book on programming using the Python language. It serves as a tutorial or guide to the Python language for a beginner audience. If all you know about computers is how to save text files, then this is the book for you.

This book provides an entertaining, informative and easy to read guide for PhD students and others on how to write and publish a scientific paper.
The book is illustrated by Jorge Cham, creator of PhD Comics (www.phdcomics.com).

A Programmer's Introduction to Mathematics uses your familiarity with ideas from programming and software to teach mathematics.
You'll learn about the central objects and theorems of mathematics, covering graphs, calculus, linear algebra, eigenvalues, optimization, and more. You'll also be immersed in the often unspoken cultural attitudes of mathematics, learning both how to read and write proofs while understanding why mathematics is the way it is. Between each technical chapter is an essay describing a different aspect of mathematical culture, and discussions of the insights and meta-insights that constitute mathematical intuition.
As you learn, we'll use new mathematical ideas to create wondrous programs, from cryptographic schemes to neural networks to hyperbolic tessellations. Each chapter also contains a set of exercises that have you actively explore mathematical topics on your own. By the end of the book, you will be able to learn mathematics on your own. In short, this book will teach you to engage with mathematics.

Eric Hayot teaches graduate students and faculty in literary and cultural studies how to think and write like a professional scholar. From granular concerns, such as sentence structure and grammar, to big-picture issues, such as adhering to genre patterns for successful research and publishing and developing productive and rewarding writing habits, Hayot helps ambitious students, newly minted Ph.D.'s, and established professors shape their work and develop their voices.
Hayot does more than explain the techniques of academic writing. He aims to adjust the writer's perspective, encouraging scholars to think of themselves as makers and doers of important work. Scholarly writing can be frustrating and exhausting, yet also satisfying and crucial, and Hayot weaves these experiences, including his own trials and tribulations, into an ethos for scholars to draw on as they write. Combining psychological support with practical suggestions for composing introductions and conclusions, developing a schedule for writing, using notes and citations, and structuring paragraphs and essays, this guide to the elements of academic style does its part to rejuvenate scholarship and writing in the humanities.

From the author of Stylish Academic Writing comes an essential new guide for writers aspiring to become more productive and take greater pleasure in their craft. Helen Sword interviewed one hundred academics worldwide about their writing background and practices. Relatively few were trained as writers, she found, and yet all have developed strategies to thrive in their publish-or-perish environment.
So how do these successful academics write, and where do they find the “air and light and time and space,” in the words of poet Charles Bukowski, to get their writing done? What are their formative experiences, their daily routines, their habits of mind? How do they summon up the courage to take intellectual risks and the resilience to deal with rejection?
Sword identifies four cornerstones that anchor any successful writing practice: Behavioral habits of discipline and persistence; Artisanal habits of craftsmanship and care; Social habits of collegiality and collaboration; and Emotional habits of positivity and pleasure. Building on this “BASE,” she illuminates the emotional complexity of the writing process and exposes the lack of writing support typically available to early-career academics. She also lays to rest the myth that academics must produce safe, conventional prose or risk professional failure. The successful writers profiled here tell stories of intellectual passions indulged, disciplinary conventions subverted, and risk-taking rewarded. Grounded in empirical research and focused on sustainable change, Air & Light & Time & Space offers a customizable blueprint for refreshing personal habits and creating a collegial environment where all writers can flourish.

☆ 《想象的共同体》作者本尼迪克特•安德森自述“越界”一生
☆ 跨地域之限，越语言之别，消文化之墙，破学科之界。
☆ 如何规避现代教育与研究自有之缚，如何于现实困顿中明理求真。
本尼迪克特•安德森，无法被标签的学术大师，以跳出椰壳碗的青蛙自况，地理的、历史的、语言的、规训的边界都无法束缚他旺盛的好奇和思考的热情。不同于一般回忆录，本书主要着眼于安德森的治学经历，作者主要评述了区域研究、田野工作、比较研究、跨学科研究四方面内容，一如既往的锋利深刻。他亲自见证了区域研究，尤其是东南亚研究的兴起；又经历了学科划分和教育体系从传统到现代的转变；近半生的时间都在东南亚三国——印度尼西亚、泰国、菲律宾实地考察研究。那个时代的学术研究面临着许多现实阻碍：语言不通，资金不足，资料困乏，政治环境。安德森和所有学者一样，面临着导师与学生、理论与实践、勤奋与机缘、权力与真相等等权衡，其反思对当下的中国学界、教育界也颇有裨益。
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《椰壳碗外的人生》是享誉世界的学者本尼迪克特•安德森的回忆性著作。书中回顾了他幼年从昆明到加州再到爱尔兰的辗转，在伊顿和剑桥的求学经历，在美国康奈尔的研究和教学经历，在东南亚印尼、泰国、菲律宾的田野调查经历，以及退休之后的种种新尝试。本书是安德森应日本友人之邀而作，于2003年前后开始构思，2009年日文版面世。英文版的出版有赖于其弟佩里•安德森的促成，然书未面世，作者便于2015年12月在印尼朗玛逝世。
回溯50余年的学术人生，安德森坦陈其以《想象的共同体》为代表的众多学术成就的灵感与起源；直击现代学术和教育体系的弊病；反思认为全球化出路单一的普遍展望，为民族主义和国际主义解锁更多可能。富有个人魅力，不论是学者还是大众读者都会在本书阅读中有所收获。
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本尼迪克特•安德森颠覆了民族主义的研究……不仅以他的理论贡献而闻名，而且也因为他对印尼、泰国、菲律宾的语言与权力的近距离检视。——《纽约时报》
安德森的所有书写都具有无畏的原创性，借助发现被忽视或被压抑的声音，挑战所有假说。他从不满足于告诉读者他们想知道的。——《卫报》（讣告）
虽说《椰壳碗外的人生》是一部学者的回忆录，但本书内容对普通读者而言也大有益处。一个学者能够婉拒三个国家的优渥条件，不断跳出舒适区，挑战新领域，不做“椰壳碗下的青蛙”，这一过程本身就足够振奋人心。——《经济学人》

Santiago Ramon y Cajal was a mythic figure in science. Hailed as the father of modern anatomy and neurobiology, he was largely responsible for the modern conception of the brain. His groundbreaking works were New Ideas on the Structure of the Nervous System and Histology of the Nervous System in Man and Vertebrates. In addition to leaving a legacy of unparalleled scientific research, Cajal sought to educate the novice scientist about how science was done and how he thought it should be done. This recently rediscovered classic, first published in 1897, is an anecdotal guide for the perplexed new investigator as well as a refreshing resource for the old pro.
Cajal was a pragmatist, aware of the pitfalls of being too idealistic -- and he had a sense of humor, particularly evident in his diagnoses of various stereotypes of eccentric scientists. The book covers everything from valuable personality traits for an investigator to social factors conducive to scientific work.
--from amazon

贯穿此书的两个主题是：土地的利用和农户家庭中再生产的过程。在本书中，费博士集中力量描述中国农民生活的基本方面。我知道，他打算在以后的研究中说明关于崇祀祖先的详细情况以及村庄和城镇中广为流传的关于信仰和知识等更复杂的体系。他还希望终有一日将自己的和同行的著作综合起来，为我们展示一幅描绘中国文化、宗教和政治体系的丰富多彩的画面。对这样一部综合性著作，像本书这样的专著当是第一步。费博士的书和他同行的贡献，将成为我们可能完成的精雕细琢的镶嵌品中的一件件珍品。

我想把这个研究报告当作一种手册，详尽叙述一种社会学观点。社会生活，特别是在建筑物或房舍的有形界限内有组织的社会生活，可以根据这种社会学观点来研究。我将描述一组特征，它们共同构成一种框架，这一框架能运用于任何具体的社会设施，无论是家庭设施、工业设施还是商业设施。本报告所使用的观点是戏剧表演的观点，其原理从舞台演出艺术原理引申而来。我将讨论个体在普通工作情境中向他人呈现他自己和他的活动的方式，他引导和控制他人对他形成的印象的方式，以及他在他人面前维持表演时可能会做或不会做的各种事情。

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

本书介绍了一种环形研究过程：思考-写作-修订-重新思考，并提出了在寻找话题、制定计划、收集资料、组织论据、起草初稿、修改润色等各个环节中贯彻以读者为中心原则的具体方法。如何将模糊的兴趣转为一个值得提出和解决的难题；如何建立一个论证，并让读者愿意接受你的观点；如何预知那些思维缜密且具有批判力的读者的不同意见，并适当地加以回应；如何撰写导言与结论，回答这个最棘手的问题：“那又怎样？”如何从读者的角度阅读自己的作品，因而知道该什么时候以及如何修改你的研究报告。