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Data analysis for business, economic...

Békés, Gábor,

Data analysis for business, economics, and policy /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data analysis for business, economics, and policy /Gábor, Békés, Central European University, Vienna and Budapest, Gábor Kézdi, University of Michigan, Ann Arbor.
作者:	Békés, Gábor,
其他作者:	Kézdi, Gábor,
面頁冊數:	xxiii, 714 pages :illustrations ;26 cm
標題:	Social sciencesResearch
ISBN:	9781108483018

Data analysis for business, economics, and policy /
Békés, Gábor,

Data analysis for business, economics, and policy /Gábor, Békés, Central European University, Vienna and Budapest, Gábor Kézdi, University of Michigan, Ann Arbor. - xxiii, 714 pages :illustrations ;26 cm

Includes bibliographical references and index.

I: Data exploration -- Origins of data -- Preparing data for analysis -- Exploratory data analysis -- Comparison and correlation -- Generalising from data -- Testing hypothesis -- II: Regression analysis -- Simple regression -- Complicated patterns and messy data -- Generalising results of a regression -- Multiple linear regression -- Modelling probabilities -- Regression with time series data -- III: Prediction -- A framework for prediction -- Model building for prediction -- Regression trees -- Random forest and boosting -- Probability prediction and classification -- Forecasting from time series date -- IV: A framework for casual analysis -- Designing and analysing experiments -- Regression and matching with observational data -- Difference-in-differences -- Methods for panel data -- Appropriate control group for panel data.

"Data analysis is a process. It starts with formulating a question and collecting appropriate data, or assessing whether the available data can help answer the question. Then comes cleaning and organizing the data, tedious but essential tasks that affect the results of the analysis as much as any other step in the process. Exploratory data analysis gives context to the eventual results and helps deciding the details of the analytical method to be applied. The main analysis consists of choosing and implementing the method to answer the question, with potential robustness checks. Along the way, correct interpretation and effective presentation of the results are crucial. Carefully crafted data visualization help summarize our findings and convey key messages. The final task is to answer the original question, with potential qualifications and directions for future inquiries"--

ISBN: 9781108483018

LCCN: 2021024817

Nat. Bib. No.: GBC0J6913bnb

Nat. Bib. Agency Control No.: 020040927UkSubjects--Topical Terms:

177711
Social sciences
--Research

LC Class. No.: H62 / .B45 2021

Dewey Class. No.: 300.72/3

Data analysis for business, economics, and policy /
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505 0 $a I: Data exploration -- Origins of data -- Preparing data for analysis -- Exploratory data analysis -- Comparison and correlation -- Generalising from data -- Testing hypothesis -- II: Regression analysis -- Simple regression -- Complicated patterns and messy data -- Generalising results of a regression -- Multiple linear regression -- Modelling probabilities -- Regression with time series data -- III: Prediction -- A framework for prediction -- Model building for prediction -- Regression trees -- Random forest and boosting -- Probability prediction and classification -- Forecasting from time series date -- IV: A framework for casual analysis -- Designing and analysing experiments -- Regression and matching with observational data -- Difference-in-differences -- Methods for panel data -- Appropriate control group for panel data.
520 $a "Data analysis is a process. It starts with formulating a question and collecting appropriate data, or assessing whether the available data can help answer the question. Then comes cleaning and organizing the data, tedious but essential tasks that affect the results of the analysis as much as any other step in the process. Exploratory data analysis gives context to the eventual results and helps deciding the details of the analytical method to be applied. The main analysis consists of choosing and implementing the method to answer the question, with potential robustness checks. Along the way, correct interpretation and effective presentation of the results are crucial. Carefully crafted data visualization help summarize our findings and convey key messages. The final task is to answer the original question, with potential qualifications and directions for future inquiries"-- $c Provided by publisher.
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