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|---|---|---|---|
| 005 | 20251210143911.0 | ||
| 008 | 251210b |||||||| |||| 00| 0 eng d | ||
| 020 | _a9780262545914 | ||
| 037 | _cTextual | ||
| 040 |
_aRTL _cRTL |
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| 084 | _qRTL | ||
| 100 |
_aHuber, Martin _9855761 |
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| 245 | _aCasual analysis: Impact evaluation and causal machine learning with application in R | ||
| 260 |
_aLondon _bThe MIT Press _c2023 |
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| 300 |
_aix, 319 p. _bIncludes bibliographical reference and index |
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| 520 | _aReasoning about cause and effect—the consequence of doing one thing versus another—is an integral part of our lives as human beings. In an increasingly digital and data-driven economy, the importance of sophisticated causal analysis only deepens. Presenting the most important quantitative methods for evaluating causal effects, this textbook provides graduate students and researchers with a clear and comprehensive introduction to the causal analysis of empirical data. | ||
| 942 |
_2CC _n0 _cTEXL |
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| 999 |
_c1466145 _d1466145 |
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