August 25, 2023 / Leave a comment
Generative artificial intelligence, or generative AI, is a technology that creates material from an existing corpus of material based on a user’s prompts. For texts, it uses a large language model that mimics a writer by combining words that statistically co-occur across a range of texts in the corpus. However, these models are prone to […]
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January 6, 2022 / Leave a comment
Scientists are concerned with the progress of research programs. A research program that doesn’t make progress in understanding the phenomena it studies wastes valuable professional time and resources. It also is a sink of resources that could be better spent improving the human condition. However, most research programs that don’t progress are unlikely to actively […]
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March 12, 2020 / 29 Comments on “Social spacing”, not “social distancing”: Deepening connections while staying safe
As the SARS-CoV-2 virus spreads across the globe to create the COVID-19 pandemic, people have been requested to stay out of public spaces and reduce interpersonal contact to reduce the transmission of the virus. This process has the unfortunate name of “social distancing“, which has connotations of removing one’s self socially and emotionally as well […]
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March 21, 2019 / Leave a comment
Renaming "statistically significant" findings as "statistically discernible" shifts the frame from meaning to perception. It also suggests that effects that are statistically "indiscernible" may be so because they truly don't exist, because they are too small to be detected with the data at hand, or because there is such imprecision in our measurements to make almost any effect imperceptible. Continue reading →
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March 1, 2018 / 5 Comments on How to justify your alpha: step by step
Do you need alpha? | Study goals? | Minimum effect size of interest? | Justify your alpha | Justify your beta | How to control for multiple comparisons? | Examples I joined a panoply of scholars who argue that it is necessary to justify your alpha (that is, the acceptable long-run proportion of false positive […]
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