Introduction to Data Analysis and Econometrics
WW Norton & Co
978-1-324-10338-7 (ISBN)
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Dr. Mark V. Siegler has taught econometrics for over 20 years and knows how to make the subject accessible to students of all backgrounds and tracks. Assuming no prior knowledge of statistics, Introduction to Data Analysis and Econometrics is written in an accessible style and focuses on developing an intuitive understanding of key concepts. This book also aims to give students the advantage of understanding the empirical methods and software tools needed in today’s workforce. Included with the interactive Norton Illumine Ebook, Smartwork online problem sets with an embedded R console help students build data skills and solve real-world problems while giving you crucial insights into the most challenging areas for your classes.
Mark V. Siegler is Professor of Economics at California State University, Sacramento, where he teaches courses in data analysis, econometrics, macroeconomics, and economic history. He has also taught at Williams College, Bates College, Harvard University, UC Berkeley, and UC Davis. He holds a BA with highest honors in Economics from UC Santa Cruz and a PhD in Economics from UC Davis, where his dissertation was awarded the Allan Nevins Prize by the Economic History Association. Siegler has published articles that explore U.S. and comparative macroeconomic history and a wide range of other topics, from the pay of international basketball players in the NBA to the use of statistical significance in economics and other disciplines. He is also the author of An Economic History of the United States: Connecting the Present with the Past (2e, Bloomsbury, 2025).
| Erscheint lt. Verlag | 1.7.2026 |
|---|---|
| Verlagsort | New York |
| Sprache | englisch |
| Maße | 206 x 254 mm |
| Gewicht | 986 g |
| Themenwelt | Wirtschaft ► Volkswirtschaftslehre ► Ökonometrie |
| ISBN-10 | 1-324-10338-8 / 1324103388 |
| ISBN-13 | 978-1-324-10338-7 / 9781324103387 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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