Mastering Metrics

From Joshua Angrist, winner of the Nobel Prize in Economics, and Jörn-Steffen Pischke, an accessible and fun guide to the essential tools of econometric research Applied econometrics, known to aficionados as 'metrics, is the original data science. 'Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. Through accessible discussion and with a dose of kung fu–themed humor, Mastering 'Metrics presents the essential tools of econometric research and demonstrates why econometrics is exciting and useful. The five most valuable econometric methods, or what the authors call the Furious Five--random assignment, regression, instrumental variables, regression discontinuity designs, and differences in differences--are illustrated through well-crafted real-world examples (vetted for awesomeness by Kung Fu Panda's Jade Palace). Does health insurance make you healthier? Randomized experiments provide answers. Are expensive private colleges and selective public high schools better than more pedestrian institutions? Regression analysis and a regression discontinuity design reveal the surprising truth. When private banks teeter, and depositors take their money and run, should central banks step in to save them? Differences-in-differences analysis of a Depression-era banking crisis offers a response. Could arresting O. J. Simpson have saved his ex-wife's life? Instrumental variables methods instruct law enforcement authorities in how best to respond to domestic abuse. Wielding econometric tools with skill and confidence, Mastering 'Metrics uses data and statistics to illuminate the path from cause to effect. Shows why econometrics is important Explains econometric research through humorous and accessible discussion Outlines empirical methods central to modern econometric practice Works through interesting and relevant real-world examples

An accessible and fun guide to the essential tools of econometric research Applied econometrics, known to aficionados as 'metrics, is the original data science. 'Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. Through accessible discussion and with a dose of kung fu–themed humor, Mastering 'Metrics presents the essential tools of econometric research and demonstrates why econometrics is exciting and useful. The five most valuable econometric methods, or what the authors call the Furious Five--random assignment, regression, instrumental variables, regression discontinuity designs, and differences in differences--are illustrated through well-crafted real-world examples (vetted for awesomeness by Kung Fu Panda's Jade Palace). Does health insurance make you healthier? Randomized experiments provide answers. Are expensive private colleges and selective public high schools better than more pedestrian institutions? Regression analysis and a regression discontinuity design reveal the surprising truth. When private banks teeter, and depositors take their money and run, should central banks step in to save them? Differences-in-differences analysis of a Depression-era banking crisis offers a response. Could arresting O. J. Simpson have saved his ex-wife's life? Instrumental variables methods instruct law enforcement authorities in how best to respond to domestic abuse. Wielding econometric tools with skill and confidence, Mastering 'Metrics uses data and statistics to illuminate the path from cause to effect. Shows why econometrics is important Explains econometric research through humorous and accessible discussion Outlines empirical methods central to modern econometric practice Works through interesting and relevant real-world examples

In addition to econometric essentials, this book covers important new extensions as well as how to get standard errors right. The authors explain why fancier econometric techniques are typically unnecessary and even dangerous.

Is your “big idea” worth pursuing? What if you could test your business model earlier in the process—before you’ve expended valuable time and resources? You’ve talked to customers. You’ve identified problems that need solving, and maybe even built a minimum viable product. But now there’s a second bridge to cross. How do you tell whether your idea represents a viable business? Do you really have to go through the whole cycle of development, failure, iteration, tweak, repeat? Scaling Lean offers an invaluable blueprint for mod­eling startup success. You’ll learn the essential metrics that measure the output of a working business model, give you the pulse of your company, communicate its health to investors, and enable you to make precise interventions when things go wrong. You’ll also learn how to: · ballpark the viability of a business model using a simple five-minute back-of-the-envelope estimation. · stop using current revenue as a measure of progress (it forces you to fly blind and, often, to overpromise to your shareholders) and instead embrace the met­ric of traction—which helps you identify the leading indicators for future business model growth. · set progressive goals that set you up for exponen­tial long-term success by implementing a staged 10X rollout strategy, like one employed by Face­book and Tesla. · stop burying your breakthrough insights in failed experiments, but rather illuminate them using two-week LEAN sprints to quickly source, rank, and test ideas. Ash Maurya, a serial entrepreneur and author of the startup cult classic Running Lean, pairs real-world examples of startups like Airbnb and Hubspot with techniques from the manufacturing world in this tacti­cal handbook for scaling with maximum efficiency and efficacy. This is vital reading for any startup founder graduating from the incubator stage.

HR metrics and organizational people-related data are an invaluable source of information from which to identify trends and patterns in order to make effective business decisions. But HR practitioners often lack the statistical and analytical know-how to fully harness the potential of this data. Predictive HR Analytics provides a clear, accessible framework for understanding and working with people analytics and advanced statistical techniques. Using the statistical package SPSS (with R syntax included), it takes readers step by step through worked examples, showing them how to carry out and interpret analyses of HR data in areas such as employee engagement, performance and turnover. Readers are shown how to use the results to enable them to develop effective evidence-based HR strategies. This second edition has been updated to include the latest material on machine learning, biased algorithms, data protection and GDPR considerations, a new example using survival analyses, and up-to-the-minute screenshots and examples with SPSS version 25. It is supported by a new appendix showing main R coding, and online resources consisting of SPSS and Excel data sets and R syntax with worked case study examples.

Master the Shiny web framework—and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, run models with parameter values of their choosing, customize visualizations, and much more. Hadley Wickham from RStudio shows data scientists, data analysts, statisticians, and scientific researchers with no knowledge of HTML, CSS, or JavaScript how to create rich web apps from R. This in-depth guide provides a learning path that you can follow with confidence, as you go from a Shiny beginner to an expert developer who can write large, complex apps that are maintainable and performant. Get started: Discover how the major pieces of a Shiny app fit together Put Shiny in action: Explore Shiny functionality with a focus on code samples, example apps, and useful techniques Master reactivity: Go deep into the theory and practice of reactive programming and examine reactive graph components Apply best practices: Examine useful techniques for making your Shiny apps work well in production

By the author of the bestselling guide, "What Every Real Estate Investor Needs to Know about Cash Flow... " (McGraw-Hill, 2004) Develop a command of the essential formulas and concepts that underlie income-property investing: * Capitalization Rate * Net Operating Income * Present Value * Debt Coverage Ratio * Internal Rate of Return and much more Here Gallinelli revisits the 37 key metrics from his "Cash Flow" book and guides you through examples that will lead you to mastery of those concepts. He then takes you beyond those formulas to the next level, with detailed case studies of four different properties: * Single-Family Rental * Renovation Project * Apartment Building * Strip Shopping Center You'll analyze these properties with him and learn to look behind the numbers, to think like a successful investor and to recognize both the opportunities and the perils you might encounter when you invest in real estate. Frank Gallinelli is the founder and President of RealData, Inc., one of the real estate industry's leading software firms since 1982. He has written several books and numerous articles on real estate investing, and teaches income-property analysis in Columbia University's Master of Science in Real Estate Development program.

An accessible, contemporary introduction to the methods for determining cause and effect in the social sciences "Causation versus correlation has been the basis of arguments--economic and otherwise--since the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It's rare that a book prompts readers to expand their outlook; this one did for me."--Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied--for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.