Category: Causative Agents

Causative Agents – Causation.org

Correlation vs Causation: Understand the Difference for Your Product

Correlation and causality can seem deceptively similar. But recognizing their differences can be the make or break between wasting efforts on low-value features and creating a product that your customers can’t stop raving about. In this piece we are going to focus on correlation and causation as it relates specifically to building digital products and understanding user behavior. Product managers,...

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Psychologists Show It’s Possible To Fix Misleading Press Releases – Without Harming Their News Value

Corrected press releases led to more accurate news, without any dip in quantity of coverage; via Adams et al, 2019[1] By Jesse Singal[2] There are many reasons why media outlets report scientifically misleading information. But one key site at which this sort of misunderstanding takes root is in the press releases that universities issue when one of their researchers has published...

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Hyped-up science erodes trust. Here’s how researchers can fight back.

In 2018, psychology PhD student William McAuliffe co-published a paper[1] in the prestigious journal Nature Human Behavior. The study’s conclusion — that people become less generous over time when they make decisions in an environment where they don’t know or interact with other people — was fairly nuanced. But the university’s press department, perhaps in an attempt to make the...

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Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data – Julia M. Rohrer, 2018

Achen, C. H. (2005). Let’s put garbage-can regressions and garbage-can probits where they belong. Conflict Management and Peace Science, 22, 327–339. Google Scholar[1] | SAGE Journals | ISI[2][3] Angrist, J. D., Pischke, J. S. (2010). The credibility revolution in empirical economics: How better research design is taking the con out of econometrics. The Journal of Economic Perspectives, 24(2), 3–30. Google...

READ MORE Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data – Julia M. Rohrer, 2018