Book picks similar to
Statistics for Nursing Research: A Workbook for Evidence-Based Practice by Susan K. Grove
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The Complete Idiot's Guide to Statistics
Robert A. Donnelly Jr. - 2004
Readerswill find information on frequency distributions; mean, median, and mode; range, variance, and standard deviation;probability; and more.-Emphasizes Microsoft Excel for number-crunching and computationsDownload a sample chapter.
The Drunkard's Walk: How Randomness Rules Our Lives
Leonard Mlodinow - 2008
From the classroom to the courtroom and from financial markets to supermarkets, Mlodinow's intriguing and illuminating look at how randomness, chance, and probability affect our daily lives will intrigue, awe, and inspire.
The Monty Hall Problem: The Remarkable Story of Math's Most Contentious Brain Teaser
Jason Rosenhouse - 2009
Imagine that you face three doors, behind one of which is a prize. You choose one but do not open it. The host--call him Monty Hall--opens a different door, alwayschoosing one he knows to be empty. Left with two doors, will you do better by sticking with your first choice, or by switching to the other remaining door? In this light-hearted yet ultimately serious book, Jason Rosenhouse explores the history of this fascinating puzzle. Using a minimum ofmathematics (and none at all for much of the book), he shows how the problem has fascinated philosophers, psychologists, and many others, and examines the many variations that have appeared over the years. As Rosenhouse demonstrates, the Monty Hall Problem illuminates fundamental mathematical issuesand has abiding philosophical implications. Perhaps most important, he writes, the problem opens a window on our cognitive difficulties in reasoning about uncertainty.
Thinking Statistically
Uri Bram - 2011
Along the way we’ll learn how selection bias can explain why your boss doesn’t know he sucks (even when everyone else does); how to use Bayes’ Theorem to decide if your partner is cheating on you; and why Mark Zuckerberg should never be used as an example for anything. See the world in a whole new light, and make better decisions and judgements without ever going near a t-test. Think. Think Statistically.
Essentials of Statistics for the Behavioral Sciences
Frederick J. Gravetter - 1991
The authors take time to explain statistical procedures so that you can go beyond memorizing formulas and gain a conceptual understanding of statistics. The authors also take care to show you how having an understanding of statistical procedures will help you comprehend published findings and will lead you to become a savvy consumer of information. Known for its exceptional accuracy and examples, this text also has a complete supplements package to support your learning.
Business Research Methods
Alan Bryman - 2004
The strengths and weaknesses of each research method are examined to help students choose an appropriate methodology, and the wider philosophical issues and ethical controversies that affect business research are discussed to help students make informed research decisions.The book examines in depth the distinction between quantitative and qualitative research techniques and how and when they should be used, and marries theoretical issues with topical case examples from a number of work-related fields (such as management, strategy, and marketing). It has also been comprehensively updated to reflect the growing use of the internet as a source of data and medium for conducting research, and places new emphasis on the student experience of research by relating the activities of real student researchers back to the research process.New to this Edition - Brand new chapter on reviewing the literature that introduces the steps involved in undertaking a critical review to help students get the most out of their reading and build a strong platform for further research. - Themed boxes that focus on examples of real, published research, key concepts, and practical tips and skills to help students grasp core principles sooner and apply their learning to new research situations. - Expanded online research guide that takes students step-by-step through their research project and provides essential research advice, checklists, templates, and case exercises to help students become more engaged and organized researchers.
Baseball Between the Numbers: Why Everything You Know About the Game Is Wrong
Jonah Keri - 2006
Properly understood, they can tell us how the teams we root for could employ better strategies, put more effective players on the field, and win more games. The revolution in baseball statistics that began in the 1970s is a controversial subject that professionals and fans alike argue over without end. Despite this fundamental change in the way we watch and understand the sport, no one has written the book that reveals, across every area of strategy and management, how the best practitioners of statistical analysis in baseball-people like Bill James, Billy Beane, and Theo Epstein-think about numbers and the game. Baseball Between the Numbers is that book. In separate chapters covering every aspect of the game, from hitting, pitching, and fielding to roster construction and the scouting and drafting of players, the experts at Baseball Prospectus examine the subtle, hidden aspects of the game, bring them out into the open, and show us how our favorite teams could win more games. This is a book that every fan, every follower of sports radio, every fantasy player, every coach, and every player, at every level, can learn from and enjoy.
The Signal and the Noise: Why So Many Predictions Fail—But Some Don't
Nate Silver - 2012
He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of FiveThirtyEight.com. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the "prediction paradox": The more humility we have about our ability to make predictions, the more successful we can be in planning for the future.In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good-or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary-and dangerous-science.Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise.
Principles and Practice of Structural Equation Modeling
Rex B. Kline - 1998
Reviewed are fundamental statistical concepts--such as correlation, regressions, data preparation and screening, path analysis, and confirmatory factor analysis--as well as more advanced methods, including the evaluation of nonlinear effects, measurement models and structural regression models, latent growth models, and multilevel SEM. The companion Web page offers data and program syntax files for many of the research examples, electronic overheads that can be downloaded and printed by instructors or students, and links to SEM-related resources.
Ant Encounters: Interaction Networks and Colony Behavior
Deborah M. Gordon - 2010
Instead, ants decide what to do based on the rate, rhythm, and pattern of individual encounters and interactions--resulting in a dynamic network that coordinates the functions of the colony. Ant Encounters provides a revealing and accessible look into ant behavior from this complex systems perspective.Focusing on the moment-to-moment behavior of ant colonies, Deborah Gordon investigates the role of interaction networks in regulating colony behavior and relations among ant colonies. She shows how ant behavior within and between colonies arises from local interactions of individuals, and how interaction networks develop as a colony grows older and larger. The more rapidly ants react to their encounters, the more sensitively the entire colony responds to changing conditions. Gordon explores whether such reactive networks help a colony to survive and reproduce, how natural selection shapes colony networks, and how these structures compare to other analogous complex systems. Ant Encounters sheds light on the organizational behavior, ecology, and evolution of these diverse and ubiquitous social insects.
Fifty Challenging Problems in Probability with Solutions
Frederick Mosteller - 1965
Selected for originality, general interest, or because they demonstrate valuable techniques, the problems are ideal as a supplement to courses in probability or statistics, or as stimulating recreation for the mathematically minded. Detailed solutions. Illustrated.
Statistical Inference
George Casella - 2001
Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.
Text Mining with R: A Tidy Approach
Julia Silge - 2017
With this practical book, you'll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media.Learn how to apply the tidy text format to NLPUse sentiment analysis to mine the emotional content of textIdentify a document's most important terms with frequency measurementsExplore relationships and connections between words with the ggraph and widyr packagesConvert back and forth between R's tidy and non-tidy text formatsUse topic modeling to classify document collections into natural groupsExamine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages
Think Stats
Allen B. Downey - 2011
This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data
Dataclysm: Who We Are (When We Think No One's Looking)
Christian Rudder - 2014
In Dataclysm, Christian Rudder uses it to show us who we truly are. For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers. In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible. Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.
