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If you have ever looked for P-values by shopping at P mart, tried to watch the Bernoulli Trials on People's Court, or think that the standard deviation is a criminal offense in six states, then you need The Cartoon Guide to Statistics to put you on the road to statistical literacy.
The Cartoon Guide to Statistics covers all the central ideas of modern statistics: the summary and display of data, probability in gambling and medicine, random variables, Bernoulli Trails, the Central Limit Theorem, hypothesis testing, confidence interval estimation, and much more--all explained in simple, clear, and yes, funny illustrations. Never again will you order the Poisson Distribution in a French restaurant!
This updated version features all new material.
Why do we use eighty-year-old metrics to understand today's economy?
The ways that statisticians and governments measure the economy were developed in the 1940s, when the urgent economic problems were entirely different from those of today. In The Measure of Progress, Diane Coyle argues that the framework underpinning today's economic statistics is so outdated that it functions as a distorting lens, or even a set of blinkers. When policymakers rely on such an antiquated conceptual tool, how can they measure, understand, and respond with any precision to what is happening in today's digital economy? Coyle makes the case for a new framework, one that takes into consideration current economic realities. Coyle explains why economic statistics matter. They are essential for guiding better economic policies; they involve questions of freedom, justice, life, and death. Governments use statistics that affect people's lives in ways large and small. The metrics for economic growth were developed when a lack of physical rather than natural capital was the binding constraint on growth, intangible value was less important, and the pressing economic policy challenge was managing demand rather than supply. Today's challenges are different. Growth in living standards in rich economies has slowed, despite remarkable innovation, particularly in digital technologies. As a result, politics is contentious and democracy strained. Coyle argues that to understand the current economy, we need different data collected in a different framework of categories and definitions, and she offers some suggestions about what this would entail. Only with a new approach to measurement will we be able to achieve the right kind of growth for the benefit of all.
Deriving business value from analytics is a challenging process. Turning data into information requires a business analyst who is adept at multiple technologies including databases, programming tools, and commercial analytics tools. This practical guide shows programmers who understand analysis concepts how to build the skills necessary to achieve business value.
Author Deanne Larson, data science practitioner and academic, helps you bridge the technical and business worlds to meet these requirements. You'll focus on developing these skills with R and Python using real-world examples. You'll also learn how to leverage methodologies for successful delivery. Learning methodology combined with open source tools is key to delivering successful business analytics and value.
This book shows you how to:
It is targeted at business students (both undergraduate and graduate) taking an introductory core course. Business analytics has grown to be a key topic in business curricula, and there is a need for stronger quantitative skills and understanding of fundamental concepts.
This second edition adds material on Tableau, a very useful software for business analytics. This supplements the tools from Excel covered in the first edition, to include Data Analysis Toolpak and SOLVER.
Finally, an introduction to statistics and business analytics for aspiring managers, leaders and decision makers who do not need to know all the details of statistical theory and just want real applications and commonsense explanations without a jumble of Greek letters and formulas. The focus is on conceptual understanding, executive-level thinking, statistical self-defense and counterintuitive phenomena that can occur. This textbook, used in the graduate core curriculum at Wharton, Harvard and other business schools, is for an MBA or undergraduate business statistics course and covers data visualization, probability, hypothesis testing, correlation, multiple regression, and includes custom Excel software for stepwise regression. The author Erol Pek z is Professor of Operations and Technology Management in the Boston University Questrom School of Business, and has also been a faculty member in the statistics departments at Harvard University, University of California, Berkeley and University of California, Los Angeles. He is the author of numerous technical articles in probability and statistics, and is the author of the book A Second Course in Probability.
The fun and friendly guide to mastering IBM's Statistical Package for the Social Sciences
Written by an author team with a combined 55 years of experience using SPSS, this updated guide takes the guesswork out of the subject and helps you get the most out of using the leader in predictive analysis.
Covering the latest release and updates to SPSS 27.0, and including more than 150 pages of basic statistical theory, it helps you understand the mechanics behind the calculations, perform predictive analysis, produce informative graphs, and more. You'll even dabble in programming as you expand SPSS functionality to suit your specific needs.
Get ready to start handling data like a pro--with step-by-step instruction and expert advice
This companion workbook to the new edition of the insightful and eloquent How to Measure Anything walks readers through sample problems and exercises in which they can master and apply the methods discussed in the book.
The book explains practical methods for measuring a variety of intangibles, including approaches to measuring customer satisfaction, organizational flexibility, technology risk, technology ROI, and other problems in business, government, and not-for-profits.
Written by recognized expert Douglas Hubbard--creator of Applied Information Economics--How to Measure Anything Workbook illustrates how the author has used his approach across various industries and how any problem, no matter how difficult, ill defined, or uncertain can lend itself to measurement using proven methods.
The guide to data and statistics for anyone who hates numbers and need a simple way to better understand what data is really telling you from former Googler and current Amazon Product Manager Neal H. Patel.
The Internet has turned us into a society that runs on data, and most of us feel out of our depth. This book helps make statistics accessible to everyone, especially those of us who find numbers intimidating, or just dislike them altogether.
Here are some of the things you'll learn in this book:
In addition, you will learn statistics the right way-using your visual brain, simple math, basic (very basic) algebra, and even a little philosophy and creative writing. With these five tools you'll learn everything from how to create and analyze your own surveys to understanding what data really means.
If you've ever said I'm bad with numbers this book is for you. If you're in a job where you need to get fluent in statistics, fast--this book is for you. Even if you just want to know how to make sense of opinion polls during the next election, this book is for you.
About the Non-Obvious Guide Series - Like having coffee with an expert.
Most business guidebooks treat you like a dummy or an idiot. Not this one. This is a short and easy-to-read guidebook filled with useful, no bullshit, only-what-you-need-to-know, immediately actionable advice for getting more done and achieving more results on LinkedIn
It is targeted at business students (both undergraduate and graduate) taking an introductory core course. Business analytics has grown to be a key topic in business curricula, and there is a need for stronger quantitative skills and understanding of fundamental concepts.
This second edition adds material on Tableau, a very useful software for business analytics. This supplements the tools from Excel covered in the first edition, to include Data Analysis Toolpak and SOLVER.
Business Statistics of the United States is a comprehensive and practical collection of data from as early as 1913 that reflects the nation's economic performance. It provides several years of annual, quarterly, and monthly data in industrial and demographic detail, including key indicators such as: gross domestic product, personal income, spending, saving, employment, unemployment, the capital stock, and more. Business Statistics of the United States is the best place to find historical perspectives on the U.S. economy.
Of equal importance to the data are the introductory highlights, extensive notes, and figures for each chapter that help users to understand the data, use them appropriately, and, if desired, seek additional information from the source agencies.
It provides a comprehensive overview of analytics in general with an emphasis on predictive analytics. Given the booming interest in analytics and data science, this book is timely and informative. It brings many terms, tools, and methods of analytics together.
The first three chapters provide an introduction to BA, importance of analytics, types of BA-descriptive, predictive, and prescriptive-along with the tools and models. Business intelligence (BI) and a case on descriptive analytics are discussed. Additionally, the book discusses on the most widely used predictive models, including regression analysis, forecasting, data mining, and an introduction to recent applications of predictive analytics-machine learning, neural networks, and artificial intelligence. The concluding chapter discusses on the current state, job outlook, and certifications in analytics.
A start-to-finish guide for realistically measuring cybersecurity risk
In the newly revised How to Measure Anything in Cybersecurity Risk, Second Edition, a pioneering information security professional and a leader in quantitative analysis methods delivers yet another eye-opening text applying the quantitative language of risk analysis to cybersecurity. In the book, the authors demonstrate how to quantify uncertainty and shed light on how to measure seemingly intangible goals. It's a practical guide to improving risk assessment with a straightforward and simple framework.
Advanced methods and detailed advice for a variety of use cases round out the book, which also includes:
Dispelling long-held beliefs and myths about information security, How to Measure Anything in Cybersecurity Risk is an essential roadmap for IT security managers, CFOs, risk and compliance professionals, and even statisticians looking for novel new ways to apply quantitative techniques to cybersecurity.