Book picks similar to
Using R for Introductory Econometrics by Florian Heiss
data-science
econometrics
economics
eco-mathstat
Learn R in a Day
Steven Murray - 2013
The book assumes no prior knowledge of computer programming and progressively covers all the essential steps needed to become confident and proficient in using R within a day. Topics include how to input, manipulate, format, iterate (loop), query, perform basic statistics on, and plot data, via a step-by-step technique and demonstrations using in-built datasets which the reader is encouraged to replicate on their computer. Each chapter also includes exercises (with solutions) to practice key skills and empower the reader to build on the essentials gained during this introductory course.
The Value of Debt in Building Wealth: Creating Your Glide Path to a Healthy Financial L.I.F.E.
Thomas J. Anderson - 2016
In The Value of Debt in Building Wealth, bestselling author Thomas J. Anderson encourages you to rethink that. You'll walk away from this book with an understanding of how you can use debt wisely to secure the financial future you envision for yourself and your family. Student loans, mortgages, lines of credit, and other forms of debt are all discussed in detail, with a focus on smart planning for those who are accumulating assets--and debt--now.Should you rent or buy? How important is liquidity? What is good versus bad debt? How much debt should you have? What debt-to-income and debt-to-asset ratios should you aim for? Fixed debt or floating debt? What's the best way of saving for college and retirement? These are big questions that deserve thorough answers because the choices you make now could influence the course of your life. This thought-provoking book will open your eyes to savvy financial strategies for achieving your goals faster and with healthier bank accounts.Explore strategies for smart debt management, explained by one of the nation's top financial advisors Gain an understanding of investment basics and key financial concepts you'll need to achieve your long-term goals Understand the risks of having debt and the potential risks of being debt-free Make financial decisions now that will maximize your wealth, freedom, and opportunity later This book is not about buying things you cannot afford. It is about liquidity, flexibility and optimizing your personal balance sheet. The Value of Debt in Building Wealth is full of ideas you can apply to your own situation--no matter what your current asset level. Read this book today and thank yourself later.
Statistical Rethinking: A Bayesian Course with Examples in R and Stan
Richard McElreath - 2015
Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.
Microsoft Excel Data Analysis and Business Modeling
Wayne L. Winston - 2004
For more than a decade, well-known consultant and business professor Wayne Winston has been teaching corporate clients and MBA students the most effective ways to use Microsoft Excel for data analysis, modeling, and decision making. Now this award-winning educator shares the best of his classroom experience in this practical, business-focused guide. Each chapter advances your data analysis and modeling expertise using real-world examples and learn-by-doing exercises. You also get all the book’s problem-and-solution files on CD—for all the practice you need to solve complex problems and work smarter with Excel.Learn how to solve real business problems with Excel!Create best, worst, and most-likely scenarios for sales Calculate how long it would take to recoup a project’s startup costs Plan personal finances, such as computing loan terms or saving for retirement Estimate a product’s demand curve Simulate stock performance over a year Determine which product mix will yield the greatest profits Interpret the effects of price and advertising on sales Assign a dollar value to customer loyalty Manage inventory and order quantities with precision Create customer service queues with short wait times Estimate the probabilities of equipment failure Model business uncertainties Get new perspectives on data with PivotTable dynamic views Help predict quarterly revenue, outcomes of sporting events, presidential elections, and more! On the CD:Practice files for all the book’s exercises Solutions for problem sets Fully searchable eBook A Note Regarding the CD or DVDThe print version of this book ships with a CD or DVD. For those customers purchasing one of the digital formats in which this book is available, we are pleased to offer the CD/DVD content as a free download via O'Reilly Media's Digital Distribution services. To download this content, please visit O'Reilly's web site, search for the title of this book to find its catalog page, and click on the link below the cover image (Examples, Companion Content, or Practice Files). Note that while we provide as much of the media content as we are able via free download, we are sometimes limited by licensing restrictions. Please direct any questions or concerns to booktech@oreilly.com.
Crunch: If the Economy's Doing So Well, Why Do I Feel So Squeezed? (BK Currents)
Jared Bernstein - 2008
In "Crunch" he answers these as well as dozens of others he has fielded from working Americans by email, on blogs, and at events where he speaks. Chances are if there's a stumper you've always wanted to ask an economist, it's solved in this book.
Discovering Statistics Using R
Andy Field - 2012
Like its sister textbook, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is enhanced by a cast of characters to help the reader on their way, hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.
Build a Career in Data Science
Emily Robinson - 2020
Industry experts Jacqueline Nolis and Emily Robinson lay out the soft skills you’ll need alongside your technical know-how in order to succeed in the field. Following their clear and simple instructions you’ll craft a resume that hiring managers will love, learn how to ace your interview, and ensure you hit the ground running in your first months at your new job. Once you’ve gotten your foot in the door, learn to thrive as a data scientist by handling high expectations, dealing with stakeholders, and managing failures. Finally, you’ll look towards the future and learn about how to join the broader data science community, leaving a job gracefully, and plotting your career path. With this book by your side you’ll have everything you need to ensure a rewarding and productive role in data science.
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
Convex Optimization
Stephen Boyd - 2004
A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.
Central Banking 101
Joseph J Wang - 2021
With a few words, the Fed can lift the stock market out of desperation and catapult it towards euphoric highs. With a few keystrokes, the Fed can conjure up trillions of dollars and fund virtually unlimited Federal spending. And with a few poor decisions, the Fed can plunge the entire world into a recession. The Federal Reserve is one of the most powerful institutions in the world, and also one of the most difficult to understand.The Fed acts through its Open Markets Desk, which sits at the heart of the global financial system as the world's ultimate and limitless provider of dollars. On behalf of policy makers, the Desk gathers market intelligence from all the major market participants, sifts through reams of internal data, and works behind the scenes keep the financial system intact. It is responsible for all of the Fed's market operations, from trillions in quantitative easing to hundreds of billions in repo and FX-swap loans. The financial crises of 2008 and 2020 abated only through the emergency interventions of the Desk.Joseph Wang spent five years studying the monetary system as a trader on the Desk. From that vantage point, Joseph saw firsthand how the Fed operates and how the financial system really works. This book is a distillation of his experience that aims to educate and demystify. After reading this book, you will understand how money is created, how the global dollar system is structured, and how it all fits into the broader financial system.The views in this book do not necessarily reflect those of the Federal Reserve Bank of New York or the Federal Reserve System.
Basic Econometrics
Damodar N. Gujarati - 1987
Because of the way the book is organized, it may be used at a variety of levels of rigor. For example, if matrix algebra is used, theoretical exercises may be omitted. A CD of data sets is provided with the text.
Econometric Analysis
William H. Greene - 1990
This title is aimed at courses in applied econometrics, political methodology, and sociological methods or a one-year graduate course in econometrics for social scientists.
Introduction to Probability
Dimitri P. Bertsekas - 2002
This is the currently used textbook for "Probabilistic Systems Analysis," an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject. It also contains, a number of more advanced topics, from which an instructor can choose to match the goals of a particular course. These topics include transforms, sums of random variables, least squares estimation, the bivariate normal distribution, and a fairly detailed introduction to Bernoulli, Poisson, and Markov processes. The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis has been just intuitively explained in the text, but is developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems. The book has been widely adopted for classroom use in introductory probability courses within the USA and abroad.
Elements of Information Theory
Thomas M. Cover - 1991
Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points.The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated referencesNow current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.
Elementary Statistics: Picturing the World
Ron Larson - 2002
Offering an approach with a visual/graphical emphasis, this text offers a number of examples on the premise that students learn best by doing. This book features an emphasis on interpretation of results and critical thinking over calculations.