Conditional design is a design method formulated by the graphic designers Luca Maurer, Jonathan Puckey, Roel Wouters and the artist Edo Paulus, in which conditions and rules of play are drawn up that invite cooperation within a 'regulated' process towards an unpredictable design or result.

Conditional design is the sequel to Operative Design. This book will further explore the operative in a more detailed, intentional, and perhaps functional manner. Spatially, the conditional is the result of the operative. It is not a blind result however. Both terms work together to satisfy a formal manipulation through a set of opportunities for elements such as connections and apertures.

& Most software practitioners deal with inherited code; this book teaches them how to optimize it & & Workbook approach facilitates the learning process & & Helps you identify where problems in a software application exist or are likely to exist

The Model Rules of Professional Conduct provides an up-to-date resource for information on legal ethics. Federal, state and local courts in all jurisdictions look to the Rules for guidance in solving lawyer malpractice cases, disciplinary actions, disqualification issues, sanctions questions and much more. In this volume, black-letter Rules of Professional Conduct are followed by numbered Comments that explain each Rule's purpose and provide suggestions for its practical application. The Rules will help you identify proper conduct in a variety of given situations, review those instances where discretionary action is possible, and define the nature of the relationship between you and your clients, colleagues and the courts.

Your one-stop guide to all things Excel 2016 Excel 2016 All-in-One For Dummies, the most comprehensive Excel reference on the market, is completely updated to reflect Microsoft's changes in the popular spreadsheet tool. It offers you everything you need to grasp basic Excel functions, such as creating and editing worksheets, setting up formulas, importing data, performing statistical functions, editing macros with Visual Basic—and beyond. In no time, your Excel skills will go from 'meh' to excellent. Written by expert Greg Harvey, who has sold more than 4.5 million copies of his previous books combined and has taught and trained extensively in Microsoft Excel, this all-encompassing guide offers everything you need to get started with Excel. From generating pivot tables and performing financial functions to performing error trapping and building and running macros—and everything in between—this hands-on, friendly guide makes working with Excel easier than ever before. Serves as the ideal reference for solving common questions and Excel pain points quickly and easily Helps to increase productivity and efficiency when working in Excel Fully updated for the new version of Excel Covers basic and more advanced Excel topics If working in Excel occasionally makes you want to scream, this will be the dog-eared, dust-free reference you'll turn to again and again.

Refactoring is gaining momentum amongst the object oriented programming community. It can transform the internal dynamics of applications and has the capacity to transform bad code into good code. This book offers an introduction to refactoring.

In this lesson we cover all the options for applying conditional formats to a workbook. Conditional formats are formatting rules that we can apply so when a cell's number changes, the format will change automatically. This is an excellent feature to use to draw a user's attention to outlying numbers, problem areas or to give a quick visual summaries of the data. We will cover: * Highlight Cell Rules * Top/Bottom Rules * Data Bars * Color Scales * Icon Sets * Using Formulas In all the above, we will also go into how to customize all the options to make any report automatically update itself according to the criteria we set. Like the other lessons, this lesson contains a link where you can download a follow along workbook and practice what is covered. Note: If you know about conditional formatting and consider yourself an Excel expert, this book is not for you. This is for Excel beginners who want to learn about this feature in plain English with no technical jargon. The images, exercises and workbook are for Excel 2013 for Windows. Most of the images and exercises will work with Excel 2010/2007 (but there may be slight differences). The workbook will not work with Excel for Mac.

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for 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 and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –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 Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.