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Library items with class number 519.50285

Data analysis with R / Tony Fischetti

No review available on this record. Title : Data analysis with R : a comprehensive guide to manipulating, analyzing, and visualizing data in R Material Type: printed text Authors: Tony Fischetti, Author Edition statement: 2nd edition Publisher: Birmingham : Packt Publishing Publication Date: 2018 Pagination: vii, 554 p. Layout: ill. Size: 24 cm ISBN (or other code): 978-1-7883-9372-0 General note: Includes index (p. 449-554) Languages : English (eng) Original Language : English (eng) Descriptors: R (Computer program language) Statistics - Data processing Class number: 519.50285 Abstract: About This Book Analyze your data using R - the most powerful statistical programming language Learn how to implement applied statistics using practical use-cases Use popular R packages to work with unstructured and structured data Who This Book Is For Budding data scientists and data analysts who are new to the concept of data analysis, or who want to build efficient analytical models in R will find this book to be useful. No prior exposure to data analysis is needed, although a fundamental understanding of the R programming language is required to get the best out of this book. What You Will Learn Gain a thorough understanding of statistical reasoning and sampling theory Employ hypothesis testing to draw inferences from your data Learn Bayesian methods for estimating parameters Train regression, classification, and time series models Handle missing data gracefully using multiple imputation Identify and manage problematic data points Learn how to scale your analyses to larger data with Rcpp, data.table, dplyr, and parallelization Put best practices into effect to make your job easier and facilitate reproducibility In Detail Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax with packages like Rcpp, ggplot2, and dplyr. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with messy data, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone's career as a data analyst. Style and approach An easy ... Contents note: RefresheR; The Shape of Data; Describing Relationships; Probability; Using Data To Reason About The World; Testing Hypotheses; Bayesian Methods; The Bootstrap; Predicting Continuous Variables; Predicting Changes with time; Sources of Data; Dealing with Missing Data; Dealing with Messy Data; Dealing with Large Data; Working with Popular R Packages; Reproducibility and Best Practices; Index Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=19065

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Barcode	Call number	Media type	Location	Section	Status
1702-002379	519.50285 Fis-Dat 2018	General Collection	Library "Max van der Stoel"	English	Due for return by 11/30/2023
1702-002380	519.50285 Fis-Dat 2018	General Collection	SEEU Library Skopje	English	Available

An introduction to modern econometrics using Stata / Christopher F. Baum

No review available on this record. Title : An introduction to modern econometrics using Stata Material Type: printed text Authors: Christopher F. Baum, Author Publisher: Stata Press Publication Date: 2006 Pagination: xviii, 341 p. : |b ill. ; |c 24 cm. Layout: ill. Size: 24 cm ISBN (or other code): 978-1-597-18013-9 General note: Includes bibliographical references (p. [321]-327) and indexes Languages : English (eng) Original Language : English (eng) Descriptors: Dataprocessing Econometrics - Computer programs Econometrie Software Class number: 519.50285 Abstract: Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata. As an expert in Stata, the author successfully guides readers from the basic elements of Stata to the core econometric topics. He first describes the fundamental components needed to effectively use Stata. The book then covers the multiple linear regression model, linear and nonlinear Wald tests, constrained least-squares estimation, Lagrange multiplier tests, and hypothesis testing of nonnested models. Subsequent chapters center on the consequences of failures of the linear regression model's assumptions. The book also examines indicator variables, interaction effects, weak instruments, underidentification, and generalized method-of-moments estimation. The final chapters introduce panel-data analysis and discrete- and limited-dependent variables and the two appendices discuss how to import data into Stata and Stata programming. Presenting many of the econometric theories used in modern empirical research, this introduction illustrates how to apply these concepts using Stata. The book serves both as a supplementary text for undergraduate and graduate students and as a clear guide for economists and financial analysts. Contents note: Notation and Typography introduction; Working with economic and financial data in stata; Organizing and handling economic data; Linear regression; Specifying the functional form; Regression with non-i.i.d. errors; Regression with indicator variables; Instrumental-variables estimators; Panel-data models; Models of discrete and limited dependent variables; Appendix a: Getting the data into stata; The basics of stata programming. Record link: https://library.seeu.edu.mk/index.php?lvl=notice_display&id=15450

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Barcode	Call number	Media type	Location	Section	Status
1702-001102	519.502 Bau-int 2006	General Collection	Library "Max van der Stoel"	English	Available