Applied Statistics and Econometrics PDF Download
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Author: Bjørnar Karlsen Kivedal
Publisher: Springer Nature
ISBN: 3031531426
Category :
Languages : en
Pages : 256
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Book Description
Author: Bjørnar Karlsen Kivedal
Publisher: Springer Nature
ISBN: 3031531426
Category :
Languages : en
Pages : 256
Get Book
Book Description
Author: Charles B Moss
Publisher: CRC Press
ISBN: 1466594098
Category : Business & Economics
Languages : en
Pages : 366
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Book Description
An Introductory Econometrics Text Mathematical Statistics for Applied Econometrics covers the basics of statistical inference in support of a subsequent course on classical econometrics. The book shows students how mathematical statistics concepts form the basis of econometric formulations. It also helps them think about statistics as more than a toolbox of techniques. Uses Computer Systems to Simplify Computation The text explores the unifying themes involved in quantifying sample information to make inferences. After developing the necessary probability theory, it presents the concepts of estimation, such as convergence, point estimators, confidence intervals, and hypothesis tests. The text then shifts from a general development of mathematical statistics to focus on applications particularly popular in economics. It delves into matrix analysis, linear models, and nonlinear econometric techniques. Students Understand the Reasons for the Results Avoiding a cookbook approach to econometrics, this textbook develops students’ theoretical understanding of statistical tools and econometric applications. It provides them with the foundation for further econometric studies.
Author: Katarzyna Kopczewska
Publisher: Routledge
ISBN: 1000079783
Category : Business & Economics
Languages : en
Pages : 725
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Book Description
This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
Author: Christian Kleiber
Publisher: Springer Science & Business Media
ISBN: 0387773185
Category : Business & Economics
Languages : en
Pages : 229
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Book Description
R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.
Author: Aygul Zagidullina
Publisher: Springer Nature
ISBN: 3030800652
Category : Business & Economics
Languages : en
Pages : 123
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Book Description
This book presents covariance matrix estimation and related aspects of random matrix theory. It focuses on the sample covariance matrix estimator and provides a holistic description of its properties under two asymptotic regimes: the traditional one, and the high-dimensional regime that better fits the big data context. It draws attention to the deficiencies of standard statistical tools when used in the high-dimensional setting, and introduces the basic concepts and major results related to spectral statistics and random matrix theory under high-dimensional asymptotics in an understandable and reader-friendly way. The aim of this book is to inspire applied statisticians, econometricians, and machine learning practitioners who analyze high-dimensional data to apply the recent developments in their work.
Author: Orley Ashenfelter
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 328
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Book Description
Every major econometric method is illustrated by a persuasive, real life example applied to real data. * Explores subjects such as sample design, which are critical to practical application econometrics.
Author: Abdelaati Daouia
Publisher: Springer Nature
ISBN: 3030732495
Category : Mathematics
Languages : en
Pages : 713
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Book Description
This book presents a unique collection of contributions on modern topics in statistics and econometrics, written by leading experts in the respective disciplines and their intersections. It addresses nonparametric statistics and econometrics, quantiles and expectiles, and advanced methods for complex data, including spatial and compositional data, as well as tools for empirical studies in economics and the social sciences. The book was written in honor of Christine Thomas-Agnan on the occasion of her 65th birthday. Given its scope, it will appeal to researchers and PhD students in statistics and econometrics alike who are interested in the latest developments in their field.
Author: Margaret Lewis
Publisher: Routledge
ISBN: 1136668705
Category : Business & Economics
Languages : en
Pages : 466
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Book Description
This book is an undergraduate text that introduces students to commonly-used statistical methods in economics. Using examples based on contemporary economic issues and readily-available data, it not only explains the mechanics of the various methods, it also guides students to connect statistical results to detailed economic interpretations. Because the goal is for students to be able to apply the statistical methods presented, online sources for economic data and directions for performing each task in Excel are also included.
Author: David P. Doane
Publisher: McGraw Hill LLC
ISBN: 9781260716283
Category : Commercial statistics
Languages : en
Pages : 0
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Book Description
"As recently as a decade ago our students used to ask us, "How do I use statistics?" Today we more often hear, "Why should I use statistics?" Applied Statistics in Business and Economics has attempted to provide real meaning to the use of statistics in our world by using real business situations and real data and appealing to your need to know why rather than just how"--
Author: Thomas Cleff
Publisher: Springer
ISBN: 303017767X
Category : Business & Economics
Languages : en
Pages : 488
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Book Description
This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it demonstrates the methods of univariate, bivariate, and multivariate statistical analysis. The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata.
