Statistics for Economists: Probability, Regression, and Data Interpretation - Softcover
Book 16 of 19: Economics
Synopsis
Every economic argument lives or dies on the data behind it.
Whether you're analyzing wage inequality, forecasting GDP, evaluating a policy intervention, or building an investment case, statistical fluency is the skill that separates rigorous analysis from informed guessing.
Statistics for Economists delivers a complete, application-driven guide to the quantitative methods that drive modern economic research. From probability theory and descriptive statistics to OLS regression, instrumental variables, and time series forecasting, each technique is explained clearly, connected to real economic questions, and grounded in the logic of evidence-based reasoning.
Inside you'll find:
- Probability, distributions, and the Central Limit Theorem — explained the way economists actually use them
- Estimation theory, confidence intervals, and hypothesis testing — from first principles to applied practice
- Simple and multiple regression, diagnostic methods, and robust standard errors
- Causal inference tools: difference-in-differences, instrumental variables, and regression discontinuity
- Limited dependent variable models — logit, probit, Tobit, and ordered regression
- Time series analysis: stationarity, ARIMA, cointegration, and error correction
- Applied case studies including demand elasticity estimation, Mincer wage equations, and policy evaluation
- A comprehensive glossary of 70+ statistical and econometric terms
This is not a math textbook. It is a practitioner's guide — written for economics students, policy analysts, financial researchers, and anyone who needs to read, interpret, and produce empirical economic work with confidence.
Statistical thinking is not optional for economists. This book makes it accessible.
"synopsis" may belong to another edition of this title.
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Paperback. Condition: new. Paperback. Every economic argument lives or dies on the data behind it.Whether you're analyzing wage inequality, forecasting GDP, evaluating a policy intervention, or building an investment case, statistical fluency is the skill that separates rigorous analysis from informed guessing.Statistics for Economists delivers a complete, application-driven guide to the quantitative methods that drive modern economic research. From probability theory and descriptive statistics to OLS regression, instrumental variables, and time series forecasting, each technique is explained clearly, connected to real economic questions, and grounded in the logic of evidence-based reasoning.Inside you'll find: Probability, distributions, and the Central Limit Theorem - explained the way economists actually use themEstimation theory, confidence intervals, and hypothesis testing - from first principles to applied practiceSimple and multiple regression, diagnostic methods, and robust standard errorsCausal inference tools: difference-in-differences, instrumental variables, and regression discontinuityLimited dependent variable models - logit, probit, Tobit, and ordered regressionTime series analysis: stationarity, ARIMA, cointegration, and error correctionApplied case studies including demand elasticity estimation, Mincer wage equations, and policy evaluationA comprehensive glossary of 70+ statistical and econometric termsThis is not a math textbook. It is a practitioner's guide - written for economics students, policy analysts, financial researchers, and anyone who needs to read, interpret, and produce empirical economic work with confidence.Statistical thinking is not optional for economists. This book makes it accessible. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798196423963
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Statistics for Economists : Probability, Regression, and Data Interpretation
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Amazon Digital Services LLC - Kdp Mai 2026, 2026
ISBN 13: 9798196423963
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Taschenbuch. Condition: Neu. Neuware - Every economic argument lives or dies on the data behind it.Whether you're analyzing wage inequality, forecasting GDP, evaluating a policy intervention, or building an investment case, statistical fluency is the skill that separates rigorous analysis from informed guessing.Statistics for Economists delivers a complete, application-driven guide to the quantitative methods that drive modern economic research. From probability theory and descriptive statistics to OLS regression, instrumental variables, and time series forecasting, each technique is explained clearly, connected to real economic questions, and grounded in the logic of evidence-based reasoning.Inside you'll find: - Probability, distributions, and the Central Limit Theorem - explained the way economists actually use them- Estimation theory, confidence intervals, and hypothesis testing - from first principles to applied practice- Simple and multiple regression, diagnostic methods, and robust standard errors- Causal inference tools: difference-in-differences, instrumental variables, and regression discontinuity- Limited dependent variable models - logit, probit, Tobit, and ordered regression- Time series analysis: stationarity, ARIMA, cointegration, and error correction- Applied case studies including demand elasticity estimation, Mincer wage equations, and policy evaluation- A comprehensive glossary of 70+ statistical and econometric termsThis is not a math textbook. It is a practitioner's guide - written for economics students, policy analysts, financial researchers, and anyone who needs to read, interpret, and produce empirical economic work with confidence.Statistical thinking is not optional for economists. This book makes it accessible. Seller Inventory # 9798196423963
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