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lgli/Martin Huber - Causal analysis Impact evaluation and causal machine learning with applications in R (University of Fribourg).pdf
Causal analysis Impact evaluation and causal machine learning with applications in R 🔍
Martin Huber University of Fribourg
English [en] · PDF · 2.4MB · 📘 Book (non-fiction) · 🚀/lgli/zlib · Save
description
From the beginning of our life as human being until its end, we are permanently confrontedwith questions about causes and effects, i.e. the consequences of doing one thing versus another.Should I rather eat croissants or muesli (the Swiss version of cereal) for breakfast to enjoy itmost? Should I rather go skiing or snowboarding to optimally benefit from the current snowconditions (snowboarding on icy slopes can be a hassle, as the fans of winter sports among usmight know)? Should I study for my statistics exam next week or will I pass anyway? This alsoapplies to broader and possibly socially more relevant questions concerning politics, businessor work life, health, and society in general, as for instance: Will more education increase myor anyone’s salary? Does a discount on a product or service increase sales? Do smoking anddrinking kill? Does a harsher punishment reduce crime? Do mothers work more when childcareis for free? Does trade and globalization increase or reduce wealth and/or income equality?Does free education foster a more egalitarian society in terms of opportunities?
Alternative filename
zlib/Mathematics/Mathematical Statistics/Martin Huber/Causal analysis Impact evaluation and causal machine learning with applications in R_21268740.pdf
date open sourced
2022-04-06
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