Designing a Fashion Collection: 16 Tutorials Using Manual and Digital Techniques

How to make digital photography lighting more creative—and less challenging! How do you master the art of lighting your photographs? Go beyond the basics, go beyond the «rules,» and get creative with the help of renowned photographer Harold Davis. In this book, Harold shows you how to break the boundaries of conventional wisdom and create unique, lively, and beautifully lit photographs. Packed with tips and tricks as well as stunning examples of the author’s creativity, this book will both inform and inspire you to create your own lighting style. Teaches you when and how to control the light in your photographs Reviews the basic “rules” of digital photography lighting and shows you how to break the rules to create your own uniquely lit images Helps you start building a lighting style of your own Includes stunning examples of the author’s photography and lighting techniques Whether you're a beginner or a seasoned digital photographer, you'll find ideas and techniques to spark your creativity.

Choosing and Using Statistics remains an invaluable guide for students using a computer package to analyse data from research projects and practical class work. The text takes a pragmatic approach to statistics with a strong focus on what is actually needed. There are chapters giving useful advice on the basics of statistics and guidance on the presentation of data. The book is built around a key to selecting the correct statistical test and then gives clear guidance on how to carry out the test and interpret the output from four commonly used computer packages: SPSS, Minitab, Excel, and (new to this edition) the free program, R. Only the basics of formal statistics are described and the emphasis is on jargon-free English but any unfamiliar words can be looked up in the extensive glossary. This new 3rd edition of Choosing and Using Statistics is a must for all students who use a computer package to apply statistics in practical and project work. Features new to this edition: Now features information on using the popular free program, R Uses a simple key and flow chart to help you choose the right statistical test Aimed at students using statistics for projects and in practical classes Includes an extensive glossary and key to symbols to explain any statistical jargon No previous knowledge of statistics is assumed

The first edition of this excellent handbook was extremely well received by both students and lecturers alike. It has helped to simplify the often complex and difficult task of choosing and using the right statistics package. This is a book for any student or professional biologist who wants to process data using a statistical package on the computer, to select appropriate methods, and extract the important information from the often confusing output that is produced. It is aimed primarily at undergraduates and masters students in the biological sciences who have to apply statistics in practical classes and projects. Such users of statistics do not have to understand either how tests work or how to do the calculations, and these aspects are not covered in the book. The new edition has been updated to cover the very latest versions of the computer packages described, expanded to include coverage for logistic regression, a more detailed consideration of multivariate analysis, data exploration and further examples of Principle Component Analysis and Discriminate Function Analysis are given. New edition will use SPSS 10.0, Minitab 13.1 and Excel 2000. New simplified version of the Key and flow chart of decisions to reach simple statistical tests. Section on multivariate techniques expanded to give further examples of PCA and DFA. Aimed at students using statistics for projects and in practical classes. Statistical jargon explained through an extensive glossary and key to symbols. Stresses the importance of experimental design, measurement of data and interpretation of results rather than an understanding of the statistical tests themselves.

Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.

Designing and Assessing Courses and Curricula reflects the most current knowledge and practice in course and curriculum design and connects this knowledge with the critical task of assessing learning outcomes at both course and curricular levels. This thoroughly revised and expanded third edition of the best-selling book positions course design as a tool for educational change and contains a wealth of new material including new chapters, case examples, and resources.

R – the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment, so as to provide a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a complete practical guide to designing and analyzing real biological research. Topics covered include: simple hypothesis testing, graphing exploratory data analysis and graphical summaries regression (linear, multi and non-linear) simple and complex ANOVA and ANCOVA designs (including nested, factorial, blocking, spit-plot and repeated measures) frequency analysis and generalized linear models. Linear mixed effects modeling is also incorporated extensively throughout as an alternative to traditional modeling techniques. The book is accompanied by a companion website www.wiley.com/go/logan/r with an extensive set of resources comprising all R scripts and data sets used in the book, additional worked examples, the biology package, and other instructional materials and links.

Lavishly illustrated with more than 450 images, A Typographic Workbook, Second Edition explains the process successful designers use to select, space, and creatively integrate fonts. This essential text demonstrates the use of type as a dynamic and expressive communication tool. This edition provides new and updated coverage of a broad range of topics–from a logical, clear historical overview of the craft to the latest digital technologies. Known for its highly interactive format, this Second Edition continues to include helpful review questions and multiple-choice quizzes, as well as many new projects and skill-building exercises that help readers immediately apply what they have learned. A Typographic Workbook, Second Edition is a valuable professional resource for working designers and an indispensable training tool for graphic design students.

Designing and Conducting Your First Interview Project Using a clear, easily followed approach, Designing and Conducting Your First Interview Project helps anyone new to the process develop the skills to conduct the most essential part of social research data collection: the interview. The book also shows how to organize, analyze, and interpret the data. This workbook provides a step-by-step template for a collaborative class experience in social science. Organized according to the steps of the deductive scientific method, it includes essential activities to take place during class after the appropriate chapter has been read. The book begins with the process of choosing a topic and proceeds through hypothesis development, interview data collection, data entry using SPSS, and elementary data analysis. The final chapter includes the formal assignment and instructions to students on how to write about their experiences in a way that will produce an excellent final paper. By selecting the hypothesis, gathering the data, and analyzing the results, students will gain an appreciation for the strengths and potential weaknesses of «knowing» things through doing quantitative social science.

Enrich your students and the institution with a high-impact practice Designing and Teaching Undergraduate Capstone Courses is a practical, research-backed guide to creating a course that is valuable for both the student and the school. The book covers the design, administration, and teaching of capstone courses throughout the undergraduate curriculum, guiding departments seeking to add a capstone course, and allowing those who have one to compare it to others in the discipline. The ideas presented in the book are supported by regional and national surveys that help the reader understand what's common, what's exceptional, what works, and what doesn't within capstone courses. The authors also provide additional information specific to different departments across the curriculum, including STEM, social sciences, humanities, fine arts, education, and professional programs. Identified as a high-impact practice by the National Survey of Student Engagement (NSSE) and the Association of American Colleges and Universities' LEAP initiative, capstone courses culminate a student's final college years in a project that integrates and applies what they've learned. The project takes the form of a research paper, a performance, a portfolio, or an exhibit, and is intended to showcase the student's very best work as a graduating senior. This book is a guide to creating for your school or department a capstone course that ties together undergraduate learning in a way that enriches the student and adds value to the college experience. Understand what makes capstone courses valuable for graduating students Discover the factors that make a capstone course effective, and compare existing programs, both within academic disciplines and across institutions Learn administrative and pedagogical techniques that increase the course's success Examine discipline-specific considerations for design, administration, and instruction Capstones are generally offered in departmental programs, but are becoming increasingly common in general education as well. Faculty and administrators looking to add a capstone course or revive an existing one need to understand what constitutes an effective program. Designing and Teaching Undergraduate Capstone Courses provides an easily digested summary of existing research, and offers expert guidance on making your capstone course successful.

A practical guide to data mining using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis—SQL and Excel—to perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this book shows you how to extract useful business information from relational databases. You'll learn the fundamental techniques before moving into the «where» and «why» of each analysis, and then learn how to design and perform these analyses using SQL and Excel. Examples include SQL and Excel code, and the appendix shows how non-standard constructs are implemented in other major databases, including Oracle and IBM DB2/UDB. The companion website includes datasets and Excel spreadsheets, and the book provides hints, warnings, and technical asides to help you every step of the way. Data Analysis Using SQL and Excel, 2nd Edition shows you how to perform a wide range of sophisticated analyses using these simple tools, sparing you the significant expense of proprietary data mining tools like SAS. Understand core analytic techniques that work with SQL and Excel Ensure your analytic approach gets you the results you need Design and perform your analysis using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to best use the tools you already know to achieve expert results.