Statistics for Data Science and Policy Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistics for Data Science and Policy Analysis write by Azizur Rahman. This book was released on 2021-04-01. Statistics for Data Science and Policy Analysis available in PDF, EPUB and Kindle. This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.
Statistics for Data Science and Policy Analysis
Statistics for Data Science and Policy Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistics for Data Science and Policy Analysis write by Azizur Rahman. This book was released on 2020-03-31. Statistics for Data Science and Policy Analysis available in PDF, EPUB and Kindle. This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.
Data Analysis for Business, Economics, and Policy
Data Analysis for Business, Economics, and Policy - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Analysis for Business, Economics, and Policy write by Gábor Békés. This book was released on 2021-05-06. Data Analysis for Business, Economics, and Policy available in PDF, EPUB and Kindle. A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Public Policy Analytics
Public Policy Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Public Policy Analytics write by Ken Steif. This book was released on 2021-08-18. Public Policy Analytics available in PDF, EPUB and Kindle. Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government.
Practical Statistics for Data Scientists
Practical Statistics for Data Scientists - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Practical Statistics for Data Scientists write by Peter Bruce. This book was released on 2017-05-10. Practical Statistics for Data Scientists available in PDF, EPUB and Kindle. Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
