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See below for a selection of the latest books from Economic statistics category. Presented with a red border are the Economic statistics books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Economic statistics books and those from many more genres to read that will keep you inspired and entertained. And it's all free!
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods. This book serves as a practitioner's guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R's machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: Offers a practical and applied introduction to the most popular machine learning methods. Takes readers through the entire modeling process; from data prep to hyperparameter tuning, model evaluation, and interpretation. Introduces readers to a wide variety of packages that make up R's machine learning stack. Uses a hands-on approach and real world data. Brad Boehmke is a data scientist at 84.51 Degrees where he wears both software developer and machine learning engineer hats. He is an Adjunct Professor at the University of Cincinnati, author of Data Wrangling with R, and creator of multiple public and private enterprise R packages. Brandon Greenwell is a data scientist at 84.51 Degrees where he works on a diverse team to enable, empower, and encourage others to successfully apply machine learning to solve real business problems. He's part of the Adjunct Graduate Faculty at Wright State University, an Adjunct Instructor at the University of Cincinnati, and the author of several R packages available on CRAN.
Social media has made charts, infographics and diagrams ubiquitous-and easier to share than ever. While such visualisations can better inform us, they can also deceive by displaying incomplete or inaccurate data, suggesting misleading patterns-or misinform by being poorly designed. Many of us are ill equipped to interpret the visuals that politicians, journalists, advertisers and even employers present each day, enabling bad actors to easily manipulate visuals to promote their own agendas. Public conversations are increasingly driven by numbers and to make sense of them, we must be able to decode and use visual information. By examining contemporary examples ranging from election-result infographics to global GDP maps and box-office record charts, How Charts Lie teaches us how to do just that.
Elements of Numerical Mathematical Economics with Excel: Static and Dynamic Optimization shows readers how to apply static and dynamic optimization theory in an easy and practical manner, without requiring the mastery of specific programming languages that are often difficult and expensive to learn. Featuring user-friendly numerical discrete calculations developed within the Excel worksheets, the book includes key examples and economic applications solved step-by-step and then replicated in Excel. After introducing the fundamental tools of mathematical economics, the book explores the classical static optimization theory of linear and nonlinear programming, applying the core concepts of microeconomics and some portfolio theory. This provides a background for the more challenging worksheet applications of the dynamic optimization theory. The book also covers special complementary topics such as inventory modelling, data analysis for business and economics, and the essential elements of Monte Carlo analysis. Practical and accessible, Elements of Numerical Mathematical Economics with Excel: Static and Dynamic Optimization increases the computing power of economists worldwide. This book is accompanied by a companion website that includes Excel examples presented in the book, exercises, and other supplementary materials that will further assist in understanding this useful framework.
Business Statistics with Solutions in R covers a wide range of applications of statistics in solving business related problems. It will introduce readers to quantitative tools that are necessary for daily business needs and help them to make evidence-based decisions. The book provides an insight on how to summarize data, analyze it, and draw meaningful inferences that can be used to improve decisions. It will enable readers to develop computational skills and problem-solving competence using the open source language, R. Mustapha Abiodun Akinkunmi uses real life business data for illustrative examples while discussing the basic statistical measures, probability, regression analysis, significance testing, correlation, the Poisson distribution, process control for manufacturing, time series analysis, forecasting techniques, exponential smoothing, univariate and multivariate analysis including ANOVA and MANOVA and more in this valuable reference for policy makers, professionals, academics and individuals interested in the areas of business statistics, applied statistics, statistical computing, finance, management and econometrics.
UNECE Countries in Figures presents a profile of social and economic indicators for each of the 56 UNECE member countries. These profiles, prepared by the UNECE Statistical Division, are intended to be of interest to readers not necessarily familiar with statistical terminology or with interpreting statistical tables. This publication includes data collected from national and international sources of official statistics. The data are for the most recent year available.
The National Accounts Studies of the ESCWA Region presents available data and ESCWA estimates of GDP at both current and constant prices, in addition to the consolidated national accounts for each ESCWA member country during a five years period, and the estimated real GDP growth for year of publication. Data is compiled from national statistical sources and by using questionnaires prepared by ESCWA. This publication is intended for economists, social researchers and planners. The publication is a reference for accurate, reliable data and statistical indicators from national sources covering entire Arab region and intended to the public and private sectors, experts and researchers in the field and regional and international organizations.
Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes, Statistical Methods with Applications to Demography and Life Insurance presents contemporary statistical techniques for analyzing life distributions and life insurance problems. It not only contains traditional material but also incorporates new problems and techniques not discussed in existing actuarial literature. The book mainly focuses on the analysis of an individual life and describes statistical methods based on empirical and related processes. Coverage ranges from analyzing the tails of distributions of lifetimes to modeling population dynamics with migrations. To help readers understand the technical points, the text covers topics such as the Stieltjes, Wiener, and Ito integrals. It also introduces other themes of interest in demography, including mixtures of distributions, analysis of longevity and extreme value theory, and the age structure of a population. In addition, the author discusses net premiums for various insurance policies. Mathematical statements are carefully and clearly formulated and proved while avoiding excessive technicalities as much as possible. The book illustrates how these statements help solve numerous statistical problems. It also includes more than 70 exercises.
The main objective of the Asia and the Pacific SDG Progress Report 2019 is to assess regional and subregional progress towards achieving the Sustainable Development Goals (SDGs) and targets. It will highlight areas of SDGs that the region has made progress and areas that need collective decisions for prioritizing acceleration or changing the trend. The report will complement other ESCAP SDG-related publications such as inequality theme study and SDG costing to inform deliberations at the Asia-Pacific Forum on Sustainable Development (APFSD), the Asia -Pacific Commission and subsequently in other occasions. The report also aim to provide an effective communication tool that foster inclusive regional consultations and effective engagement of the stakeholders including media and civil society. The report will utilize cross-nationally comparable data from ESCAP database on the proposed SDGs indicator framework and when necessary use supplementary statistics available at the regional and sub-regional levels. In addition to regional and subregional SDG progress analysis, the 2019 version of the regional SDG progress report will provide insights about data availability for SDG monitoring and identifies gapes and provides recommendations for investing in statistical development to fill in such gaps.
The 2019 edition of the State of Commodity Dependence contains 189 individual country profiles, each comprising 30 indicators mostly related to the four main dimensions of commodity dependence, namely: merchandise and commodity export dependence - Commodity import dependence - key socio-economic indicators - other structural indicators. As commodity dependence tends to negatively affect poverty alleviation and food security, a set of indicators is included to help monitor trends in these areas. For each individual country, 1995 is used as the historical reference year. Moreover an in-depth analysis of commodity dependence in the 189 countries is presented at the beginning of the report with key messages.
A collection of proofs of fundamental theorems, this volume utilizes a format that is exhaustive and consistent. Every result covered in ``Econometrics''is proved as well as stated. One notation system is used throughout the volume. The topics included in the book cover such areas as estimations and testing in linear regression models under various sets of assumptions, and estimation and testing in simultaneous equations models. The latter subject is treated more extensively than in most econometrics books, and the entire volume is characterized by its rigorous level of examination.
Originally published in 1978. This book is designed to enable students on main courses in economics to comprehend literature which employs econometric techniques as a method of analysis, to use econometric techniques themselves to test hypotheses about economic relationships and to understand some of the difficulties involved in interpreting results. While the book is mainly aimed at second-year undergraduates undertaking courses in applied economics, its scope is sufficiently wide to take in students at postgraduate level who have no background in econometrics - it integrates fully the mathematical and statistical techniques used in econometrics with micro- and macroeconomic case studies.
Originally published in 1929. This balanced combination of fieldwork, statistical measurement, and realistic applications shows a synthesis of economics and political science in a conception of an organic relationship between the two sciences that involves functional analysis, institutional interpretation, and a more workmanlike approach to questions of organization such as division of labour and the control of industry. The treatise applies the test of fact through statistical analysis to economic and political theories for the quantitative and institutional approach in solving social and industrial problems. It constructs a framework of concepts, combining both economic and political theory, to systematically produce an original statement in general terms of the principles and methods for statistical fieldwork. The separation into Parts allows selective reading for the methods of statistical measurement; the principles and fallacies of applying these measures to economic and political fields; and the resultant construction of a statistical economics and politics. Basic statistical concepts are described for application, with each method of statistical measurement illustrated with instances relevant to the economic and political theory discussed and a statistical glossary is included.