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2 changes: 1 addition & 1 deletion chapters/12/2/Causality.ipynb
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"cell_type": "markdown",
"metadata": {},
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"Our methods for comparing two samples have a powerful use in the analysis of randomized controlled experiments. Since the treatment and control groups are assigned randomly in such experiements, differences in their outcomes can be compared to what would happen just due to chance if the treatment had no effect at all. If the observed differences are more marked than what we would predict as purely due to chance, we will have evidence of *causation*. Because of the unbiased assignment of individuals to the treatment and control groups, differences in the outcomes of the two groups can be ascribed to the treatment.\n",
"Our methods for comparing two samples have a powerful use in the analysis of randomized controlled experiments. Since the treatment and control groups are assigned randomly in such experiments, differences in their outcomes can be compared to what would happen just due to chance if the treatment had no effect at all. If the observed differences are more marked than what we would predict as purely due to chance, we will have evidence of *causation*. Because of the unbiased assignment of individuals to the treatment and control groups, differences in the outcomes of the two groups can be ascribed to the treatment.\n",
"\n",
"The key to the analysis of randomized controlled experiments is understanding exactly how chance enters the picture. This helps us set up clear null and alternative hypotheses. Once that's done, we can simply use the methods of the previous sections to complete the analysis.\n",
"\n",
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