- Last 7 days
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www.slideshare.net www.slideshare.net
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Stephen Senn. (19:12:01 UTC). De Finetti meets Popper [Data & Analytics]. https://www.slideshare.net/StephenSenn1/de-finetti-meets-popper
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twitter.com twitter.com
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ReconfigBehSci. (2021, February 1). @islaut1 @richarddmorey I think of strength of inference resting on P(not E|not H) (for coronavirus case). Search determines the conditional probability (and by total probability of course prob of evidence) but it isn’t itself the evidence. So, was siding with R. against what I thought you meant ;-) [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1356216290847944706
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twitter.com twitter.com
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ReconfigBehSci. (2021, February 2). @MichaelPaulEdw1 @islaut1 @ToddHorowitz3 @richarddmorey @MaartenvSmeden as I just said to @islaut1 if you want to force the logical contradiction you move away entirely from all of the interesting cases of inference from absence in everyday life, including the interesting statistical cases of, for example, null findings—So I think we now agree? [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1356530759016792064
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link.springer.com link.springer.com
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Cousins, R. D. (2017). The Jeffreys–Lindley paradox and discovery criteria in high energy physics. Synthese, 194(2), 395–432. https://doi.org/10.1007/s11229-014-0525-z
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web.stanford.edu web.stanford.edu
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Freedman, D. A. (n.d.). Ecological Inference and the Ecological Fallacy. 7.
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- Feb 2021
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academic.oup.com academic.oup.com
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Blakely, Tony, John Lynch, Koen Simons, Rebecca Bentley, and Sherri Rose. ‘Reflection on Modern Methods: When Worlds Collide—Prediction, Machine Learning and Causal Inference’. International Journal of Epidemiology 49, no. 6 (1 December 2020): 2058–64. https://doi.org/10.1093/ije/dyz132.
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psyarxiv.com psyarxiv.com
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Perez Santangelo, A., & Solovey, G. (2020, November 9). Time to Shine: Reliable Response-Timing Using R-Shiny for Online Experiments. https://doi.org/10.31234/osf.io/nuxdg
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- Jan 2021
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yanirseroussi.com yanirseroussi.com
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While no serious climate scientist doubts the fact that human activities are causing climate change, this can’t be proved through experimentation on another Earth.
In both cases, the answers should be clear when looking at the evidence and the mechanisms at play without an ideological bias
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- Dec 2020
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medium.com medium.com
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“provenance” — broadly, where did data arise, what inferences were drawn from the data, and how relevant are those inferences to the present situation? While a trained human might be able to work all of this out on a case-by-case basis, the issue was that of designing a planetary-scale medical system that could do this without the need for such detailed human oversight.
Data Provenance
The discipline of thinking about:
(1) where did the data arise? (2) what inferences were drawn (3) how relevant are those inferences to the present situation?
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- Oct 2020
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seeing-theory.brown.edu seeing-theory.brown.edu
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Kunin, D. (n.d.). Seeing Theory. Retrieved October 27, 2020, from http://seeingtheory.io
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- Aug 2020
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www.youtube.com www.youtube.com
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The Alan Turing Institute: Causal Inference, Causal Decision Making Under Uncertainty | CogX 2020. (2020, June 25). https://www.youtube.com/watch?v=JAGRHbDLvUs
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psyarxiv.com psyarxiv.com
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Speelman, C., & McGann, M. (2020). Statements about the Pervasiveness of Behaviour Require Data about the Pervasiveness of Behaviour [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/bxzm4
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Young, J.-G., Cantwell, G. T., & Newman, M. E. J. (2020). Robust Bayesian inference of network structure from unreliable data. ArXiv:2008.03334 [Physics, Stat]. http://arxiv.org/abs/2008.03334
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Manski, C. F., & Molinari, F. (2020). Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem (Working Paper No. 27023; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27023
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- Jul 2020
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Leininger, A., & Schaub, M. (2020). Voting at the dawn of a global pandemic [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/a32r7
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osf.io osf.io
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Méndez, P. F. (2020). Blue uncertainty: Warding off systemic risks in the Anthropocene – Lessons from COVID-19 [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/z2br5
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- Jun 2020
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Zhang, L., & Peixoto, T. P. (2020). Statistical inference of assortative community structures. ArXiv:2006.14493 [Cond-Mat, Physics:Physics, Stat]. http://arxiv.org/abs/2006.14493
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www.lshtm.ac.uk www.lshtm.ac.uk
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Causal inference isn’t what you think it is. (n.d.). LSHTM. Retrieved June 26, 2020, from https://www.lshtm.ac.uk/newsevents/events/causal-inference-isnt-what-you-think-it
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academic.oup.com academic.oup.com
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Marshall, B. D. L., & Galea, S. (2015). Formalizing the Role of Agent-Based Modeling in Causal Inference and Epidemiology. American Journal of Epidemiology, 181(2), 92–99. https://doi.org/10.1093/aje/kwu274
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- Mar 2020
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theconversation.com theconversation.com
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They reflect an area of science known as biological taxonomy, the classification of organisms into different groups.
But these facts bear little consequence in day-to-day interactions hence their exotic status. People confuse less and fewer because using one or the other rarely changes the interaction. Calling a cashew a seed or a nut really doesn't change much.
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- Jul 2018
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am207.github.io am207.github.io
- Dec 2016
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plantsinaction.science.uq.edu.au plantsinaction.science.uq.edu.au
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Inference: Leaves show great variations to spread chloroplast over a large surface area to maximize light absorption. At the same time, internal leaf structure needs to optimize carbon exchange. Especially since carbon fixation is rate limiting. Therefore, there should be a relationship between leaf area and leaf structure. How strong is this relationship?
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- Sep 2016
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lawrenceacademy-my.sharepoint.com lawrenceacademy-my.sharepoint.com
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discover how these mountain people identified relatives and friends
tried to discover and learn from the people form the culture
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Rather than studying people, ethnography means learning from people
involves making inferences and knowing back round knowledge
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- May 2015
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nfllabor.files.wordpress.com nfllabor.files.wordpress.com
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without Brady‟ s knowledge and approval
Brady needed no knowledge of this activity. Safe to assume he told them that he likes 12.5 and that he is upset when they are inflated higher e.g. 16 psi.
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“You good Jonny boy? ”; “You doing good?
Again, this is another negative inference that can easily be considered normal behavior in this situation.
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speaking by telephone three times in the hours after the game for a total of 37 minutes and 11 seconds
Seemingly normal whether guilty or innocent.
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McNally‟s knowledg e that Brady prefers footballs inflat ed at the low end of the permissible range and his express request that the referee set the balls at a 12.5 psi level
If there have been instances of balls being inflated by referees to 16, it is plausible that Brady would instruct the guy who gives the balls to the officials to make sure they stay at 12.5.
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Brady and Jastremski shortly after suspicions of ball tampering became public on January 1
This is another inference to the negative. If you are implicated in something with someone who works with/for you is it a natural reaction to stop communicating? Is it more natural to speak with that person? How does behavior change when the entire global media is involved?
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