June 2021
Beginner to intermediate
358 pages
10h
English
Content preview from Behavioral Data Analysis with R and Python
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Bibliography
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Aberson, Christopher L. Applied Power Analysis for the Behavioral Sciences. Abingdon, UK: Routledge, 2019.
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Angrist, Joshua D., and Jörn-Steffen Pischke. Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton, NJ: Princeton University Press, 2009. A go-to reference for applied econometrics, with graduate-level math and statistics.
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Angrist, Joshua D., and Jörn-Steffen Pischke. Mastering “Metrics”: The Path from Cause to Effect. Princeton, NJ: Princeton University Press, 2014. A more accessible version of their 2009 classic, with added Kung Fu Panda references!
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Antonio, Nuno, Ana de Almeida, and Luis Nunes. “Hotel booking demand datasets.” Data in Brief 22 (Feb. 2019): 41-49. https://doi.org/10.1016/j.dib.2018.11.126.
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Bertrand, Marianne, and Sendhil Mullainathan. “Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination.” American Economic Review 94, no. 4 (2004): 991-1013.
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Cohen, Jacob. Statistical Power Analysis for the Behavioral Sciences, 2nd Edition. Abingdon, UK: Routledge, 2013. A classic on power analysis. Like most classics, it is somewhat dated on computer implementation, but still a great resource to think more deeply about what statistical power is.
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Cunningham, Scott. Causal Inference: The Mixtape. New Haven, CT: Yale University Press, 2021. A very accessible variation on the Angrist/Pischke books, still targeted primarily to academics.
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Davison, A. C., and D. V. Hinkley. Bootstrap ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.