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A First Course in Design and Analysis of Experiments
"Oehlert’s text is suitable for either a service course for non-statistics graduate students or for statistics majors. Unlike most texts for the one-term grad/upper level course on experimental design, Oehlert’s new book offers a superb balance of both analysis and design, presenting three practical themes to students: when to use various designs; how to analyze the results; how to recognize various design options. Also, unlike other older texts, the book is fully oriented toward the use of statistical software in analyzing experiments"--Publisher's description.
A First Course in Design and Analysis of Experiments
Oehlert's text is suitable for either a service course for non-statistics graduate students or for statistics majors. Unlike most texts for the one-term grad/upper level course on experimental design, Oehlert's new book offers a superb balance of both analysis and design, presenting three practical themes to students: • when to use various designs • how to analyze the results • how to recognize various design options Also, unlike other older texts, the book is fully oriented toward the use of statistical software in analyzing experiments.
Strength in Numbers: The Rising of Academic Statistics Departments in the U. S.
Statistical science as organized in formal academic departments is relatively new. With a few exceptions, most Statistics and Biostatistics departments have been created within the past 60 years. This book consists of a set of memoirs, one for each department in the U.S. created by the mid-1960s. The memoirs describe key aspects of the department’s history -- its founding, its growth, key people in its development, success stories (such as major research accomplishments) and the occasional failure story, PhD graduates who have had a significant impact, its impact on statistical education, and a summary of where the department stands today and its vision for the future. Read here all about how departments such as at Berkeley, Chicago, Harvard, and Stanford started and how they got to where they are today. The book should also be of interests to scholars in the field of disciplinary history.
Case Studies in Environmental Statistics
This book offers a set of case studies exemplifying the broad range of statis tical science used in environmental studies and application. The case studies can be used for graduate courses in environmental statistics, as a resource for courses in statistics using genuine examples to illustrate statistical methodol ogy and theory, and for courses in environmental science. Not only are these studies valuable for teaching about an essential cross-disciplinary activity but they can also be used to spur new research along directions exposed in these examples. The studies reported here resulted from a program of research carried on by the National Institute of Statistical Sciences (NISS) during th...
The Art of Randomness
Harness the power of randomness (and Python code) to solve real-world problems in fun, hands-on experiments—from simulating evolution to encrypting messages to making machine-learning algorithms! The Art of Randomness is a hands-on guide to mastering the many ways you can use randomized algorithms to solve real programming and scientific problems. You’ll learn how to use randomness to run simulations, hide information, design experiments, and even create art and music. All you need is some Python, basic high school math, and a roll of the dice. Author Ronald T. Kneusel focuses on helping you build your intuition so that you’ll know when and how to use random processes to get things don...
Business Experiments with R
BUSINESS EXPERIMENTS with R A unique text that simplifies experimental business design and is dedicated to the R language Business Experiments with R offers a guide to, and explores the fundamentals of experimental business designs. The book fills a gap in the literature to provide a text on the topic of business statistics that addresses issues such as small samples, lack of normality, and data confounding. The author—a noted expert on the topic—puts the focus on the A/B tests (and their variants) that are widely used in industry, but not typically covered in business statistics textbooks. The text contains the tools needed to design and analyze two-treatment experiments (i.e., A/B test...
Adventures in Financial Data Science
Graham Giller is one of Wall Street's original data scientists. Starting his career at Morgan Stanley in the UK, he was an early member of Peter Muller's famous PDT group and went on to run his own investment firm. He was Bloomberg LP's original data science hire and set up the data science team in the Global Data division there. He them moved to J.P. Morgan to take the role of Chief Data Scientist, New Product Development, and was subsequently Head of Data Science Research at J.P. Morgan and Head of Primary Research at Deutsche Bank. This book is briefly a biography but mostly a narrative of Graham's research in the fields of financial, economic, and alternative data. It contains extensive ...
The Practice of Data Analysis
This collection of essays brings together many of the world's most distinguished statisticians to discuss a wide array of the most important recent developments in data analysis. The book honors John W. Tukey, one of the most influential statisticians of the twentieth century, on the occasion of his eightieth birthday. Contributors, some of them Tukey's former students, use his general theoretical work and his specific contributions to Exploratory Data Analysis as the point of departure for their papers. They cover topics from "pure" data analysis, such as gaussianizing transformations and regression estimates, and from "applied" subjects, such as the best way to rank the abilities of chess ...
Essays On Trading Strategy
This book directly focuses on finding optimal trading strategies in the real world and supports that with a well-defined theoretical foundation that allows trading strategy problems to be solved. Critically, it also delivers a menu of actual solutions that can be applied by traders with various risk profiles and objectives in markets that exhibit substantial tail risk. It shows how the Markowitz approach leads to excessive risk taking, and trader underperformance, in the real world. It summarizes the key features of Utility Theory, the deficiencies of the Sharpe Ratio as a statistic, and develops an optimal decision theory with fully developed examples for both 'Normal' and leptokurtotic distributions.
