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Tom Moultrie. (2021, December 12). Given the comedic misinterpretation of the South African testing data offered by @BallouxFrancois (and many others!) last night ... I offer some tips having contributed to the analysis of the testing data for the @nicd_sa since April last year. (1/6) [Tweet]. @tomtom_m. https://twitter.com/tomtom_m/status/1469954015932915718

Tran, V.-T., Perrodeau, E., Saldanha, J., Pane, I., & Ravaud, P. (2021). Efficacy of COVID-19 Vaccination on the Symptoms of Patients With Long COVID: A Target Trial Emulation Using Data From the ComPaRe e-Cohort in France (SSRN Scholarly Paper ID 3932953). Social Science Research Network. https://papers.ssrn.com/abstract=3932953

Are 7 French fries too many?. A causal inference explainer | by Ellie Murray | Medium. (n.d.). Retrieved August 22, 2021, from https://medium.com/@EpiEllie/are-7-french-fries-too-many-d6226e78dc1f

Dunn, E. W., Chen, L., Proulx, J. D. E., Ehrlinger, J., & Savalei, V. (2021). Can Researchers’ Personal Characteristics Shape Their Statistical Inferences? Personality and Social Psychology Bulletin, 47(6), 969–984. https://doi.org/10.1177/0146167220950522

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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

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

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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In both cases, the answers should be clear when looking at the evidence and the mechanisms at play without an ideological bias

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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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.

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?

tried to discover and learn from the people form the culture

involves making inferences and knowing back round knowledge

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.

Again, this is another negative inference that can easily be considered normal behavior in this situation.

Seemingly normal whether guilty or innocent.

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.

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?