
Sign up to save your podcasts
Or
When you deal with statistical science, causal inference, measurement, philosophy, rationalism, discourse, and similar, there's some different questions that pop up, and I think I’ve discovered that there's a shared answer behind a lot of the questions that I have been thinking about. In this post, I will briefly present the questions, and then in a followup post I will try to give my answer for them.
Why are people so insistent about outliers?
A common statistical method is to assume an outcome is due to a mixture of observed factors and unobserved factors, and then model how much of an effect the observed factors have, and attribute all remaining variation to unobserved factors. And then one makes claims about the effects of the observed factors.
But some people then pick an outlier and demand an explanation for that outlier, rather than just accepting the general statistical finding:
---
Outline:
(00:28) Why are people so insistent about outliers?
(01:55) Why isn’t factor analysis considered the main research tool?
(02:58) Why do people want “the” cause?
(03:33) Why are people dissatisfied with GWAS?
(04:16) What value does qualitative research provide?
(05:17) What's the distinction between personality disorders and “normal” personality variation?
(06:14) What is autism?
(07:29) What is gifted child syndrome/twice-exceptionals?
(07:52) What's up with psychoanalysts?
(08:22) Why are some ideas more “robust” than others?
(09:13) How can probability theory model bag-like dynamics?
(09:58) Why would progressivism have paradoxical effects on diversity?
(10:40) Why don’t people care about local validity and coherence?
(11:27) How does commonsense reasoning avoid the principle of explosion?
(11:49) What's wrong with symptom treatment?
(12:10) Why does medicine have such funky qualitative reasoning?
(12:39) What does it mean to explain a judgement?
(13:18) Why do people seem to be afraid of measuring things?
(13:47) Why is there no greater consensus for large-scale models?
(14:28) Can we “rescue” the notion of objectivity?
(15:00) What lessons can we even learn from long-tailedness?
(15:39) Perception is logaritmic; doesn’t this by default solve a lot of problems?
(18:37) All of this may be wrong
The original text contained 4 images which were described by AI.
---
First published:
Source:
Narrated by TYPE III AUDIO.
---
Images from the article:
Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
When you deal with statistical science, causal inference, measurement, philosophy, rationalism, discourse, and similar, there's some different questions that pop up, and I think I’ve discovered that there's a shared answer behind a lot of the questions that I have been thinking about. In this post, I will briefly present the questions, and then in a followup post I will try to give my answer for them.
Why are people so insistent about outliers?
A common statistical method is to assume an outcome is due to a mixture of observed factors and unobserved factors, and then model how much of an effect the observed factors have, and attribute all remaining variation to unobserved factors. And then one makes claims about the effects of the observed factors.
But some people then pick an outlier and demand an explanation for that outlier, rather than just accepting the general statistical finding:
---
Outline:
(00:28) Why are people so insistent about outliers?
(01:55) Why isn’t factor analysis considered the main research tool?
(02:58) Why do people want “the” cause?
(03:33) Why are people dissatisfied with GWAS?
(04:16) What value does qualitative research provide?
(05:17) What's the distinction between personality disorders and “normal” personality variation?
(06:14) What is autism?
(07:29) What is gifted child syndrome/twice-exceptionals?
(07:52) What's up with psychoanalysts?
(08:22) Why are some ideas more “robust” than others?
(09:13) How can probability theory model bag-like dynamics?
(09:58) Why would progressivism have paradoxical effects on diversity?
(10:40) Why don’t people care about local validity and coherence?
(11:27) How does commonsense reasoning avoid the principle of explosion?
(11:49) What's wrong with symptom treatment?
(12:10) Why does medicine have such funky qualitative reasoning?
(12:39) What does it mean to explain a judgement?
(13:18) Why do people seem to be afraid of measuring things?
(13:47) Why is there no greater consensus for large-scale models?
(14:28) Can we “rescue” the notion of objectivity?
(15:00) What lessons can we even learn from long-tailedness?
(15:39) Perception is logaritmic; doesn’t this by default solve a lot of problems?
(18:37) All of this may be wrong
The original text contained 4 images which were described by AI.
---
First published:
Source:
Narrated by TYPE III AUDIO.
---
Images from the article:
Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
26,409 Listeners
2,387 Listeners
7,908 Listeners
4,131 Listeners
87 Listeners
1,457 Listeners
9,042 Listeners
87 Listeners
388 Listeners
5,432 Listeners
15,216 Listeners
474 Listeners
122 Listeners
75 Listeners
458 Listeners