Statistics, Philosophy & the fine art of decision making

The connected worlds of Statistics & Philosophy

by Jahnavi Ghelani
1 min read

Tags

  • philosophy
  • statistics

I enjoy reading ๐˜€๐˜๐—ฎ๐˜๐—ถ๐˜€๐˜๐—ถ๐—ฐ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—ฝ๐—ต๐—ถ๐—น๐—ผ๐˜€๐—ผ๐—ฝ๐—ต๐˜† but I hadnโ€™t seen these combined in a single book/paper until I came across Zoltan Varjuโ€™s compilation. And Iโ€™ve been thoroughly enjoying it! ๐—ข๐—ป๐—ฒ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—น๐—ฒ๐˜€๐˜€ ๐˜๐—ฎ๐—น๐—ธ๐—ฒ๐—ฑ ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐˜๐—ฟ๐—ฎ๐—ถ๐˜๐˜€ ๐—ผ๐—ณ ๐—ฎ๐—ป ๐—ฎ๐—ฑ๐—ฒ๐—ฝ๐˜ ๐˜€๐˜๐—ฎ๐˜๐—ถ๐˜€๐˜๐—ถ๐—ฐ๐—ถ๐—ฎ๐—ป (๐—ผ๐—ฟ ๐—ฎ๐—ป๐—ฎ๐—น๐˜†๐˜€๐˜ s๐—ฐ๐—ถ๐—ฒ๐—ป๐˜๐—ถ๐˜€๐˜) ๐—ถ๐˜€ ๐—ด๐—ผ๐—ผ๐—ฑ ๐—ฑ๐—ฒ๐—ฐ๐—ถ๐˜€๐—ถ๐—ผ๐—ป ๐—บ๐—ฎ๐—ธ๐—ถ๐—ป๐—ด ๐˜€๐—ธ๐—ถ๐—น๐—น๐˜€.

The road to conclusions is paved with innumerable decisions. To list a few:

  • ๐Ÿ” selecting the analysis approach
  • ๐Ÿ” designing the feature set - variables, aggregation levels, handling inter-feature relations
  • ๐Ÿ” whether to scale/normalize/weigh features & how
  • ๐Ÿ” how to effectively validate results
  • ๐Ÿ” identifying impactful improvements
  • ๐Ÿ” how to future-proof the model to update with new data
    & so on.

Each decision branches into more choices, but you get the idea.

๐—ช๐—ต๐—ฎ๐˜ ๐—น๐—ถ๐—ฒ๐˜€ ๐—ฏ๐—ฒ๐—ต๐—ถ๐—ป๐—ฑ ๐˜๐—ต๐—ถ๐˜€ ๐—ฑ๐—ฒ๐—ฐ๐—ถ๐˜€๐—ถ๐—ผ๐—ป ๐—บ๐—ฎ๐—ธ๐—ถ๐—ป๐—ด, ๐—ถ๐—ป ๐—ฎ๐—ฑ๐—ฑ๐—ถ๐˜๐—ถ๐—ผ๐—ป ๐˜๐—ผ ๐˜€๐—ผ๐˜‚๐—ป๐—ฑ ๐—บ๐—ฎ๐˜๐—ต๐—ฒ๐—บ๐—ฎ๐˜๐—ถ๐—ฐ๐—ฎ๐—น ๐—ฎ๐—ป๐—ฑ ๐˜€๐˜๐—ฎ๐˜๐—ถ๐˜€๐˜๐—ถ๐—ฐ๐—ฎ๐—น ๐—ธ๐—ป๐—ผ๐˜„๐—น๐—ฒ๐—ฑ๐—ด๐—ฒ, ๐—ถ๐˜€ t๐—ต๐—ฒ ๐˜„๐—ฎ๐˜† ๐˜„๐—ฒ ๐˜๐—ต๐—ถ๐—ป๐—ธ ๐—ฎ๐—ป๐—ฑ ๐—ฟ๐—ฒ๐—ฎ๐˜€๐—ผ๐—ป.

Lights, camera, enter: Philosophy ๐Ÿง 

How does an analyst factor uncertainty? What assumptions do we make to model real world behaviour? How do we draw conclusions from imperfect models? ๐—”๐—น๐—น ๐—ผ๐—ณ ๐˜๐—ต๐—ถ๐˜€ ๐—ต๐—ผ๐—น๐—ฑ๐˜€ ๐—ฏ๐—ฎ๐˜€๐—ถ๐˜€ ๐—ถ๐—ป ๐—ต๐—ผ๐˜„ ๐˜„๐—ฒ ๐—พ๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ป๐—ฑ ๐˜๐—ฎ๐—ถ๐—น๐—ผ๐—ฟ ๐—ผ๐˜‚๐—ฟ ๐˜๐—ต๐—ฒ๐—ผ๐—ฟ๐—ฒ๐˜๐—ถ๐—ฐ๐—ฎ๐—น ๐—ธ๐—ป๐—ผ๐˜„๐—น๐—ฒ๐—ฑ๐—ด๐—ฒ ๐˜๐—ผ ๐—ฐ๐—ฟ๐—ฒ๐—ฎ๐˜๐—ฒ ๐—ฑ๐—ฎ๐˜๐—ฎ-๐—ฏ๐—ฎ๐—ฐ๐—ธ๐—ฒ๐—ฑ ๐˜€๐—ผ๐—น๐˜‚๐˜๐—ถ๐—ผ๐—ป๐˜€.

I discovered two brilliant terms that Box aptly calls โ€œpathologiesโ€:

  • ๐Ÿงฎ Cookbookery: mindless application of statistical techniques - a plague in todayโ€™s data science community.
  • ๐Ÿงฎ Mathemastery: theory for theoryโ€™s sake without practical application.

Theory and practice must always inform each other for genuine progress.

๐—œ๐—ณ ๐˜†๐—ผ๐˜‚ ๐—ฎ๐—ฟ๐—ฒ ๐˜€๐—ผ๐—บ๐—ฒ๐—ผ๐—ป๐—ฒ ๐˜„๐—ต๐—ผ ๐—ฎ๐—ป๐—ฎ๐—น๐˜†๐˜‡๐—ฒ๐˜€ ๐—ฑ๐—ฎ๐˜๐—ฎ, ๐—œ ๐˜‚๐—ฟ๐—ด๐—ฒ ๐˜†๐—ผ๐˜‚ ๐˜๐—ผ ๐—ต๐—ผ๐—ป๐—ฒ ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฟ๐—ฒ๐—ณ๐—น๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป + ๐—ฐ๐—ฟ๐—ถ๐˜๐—ถ๐—ฐ๐—ฎ๐—น ๐—ฟ๐—ฒ๐—ฎ๐˜€๐—ผ๐—ป๐—ถ๐—ป๐—ด ๐˜€๐—ธ๐—ถ๐—น๐—น๐˜€. ๐—”๐˜€๐—ธ:

  • H๐—ผ๐˜„ ๐—ฑ๐—ผ ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฐ๐—ต๐—ผ๐—ถ๐—ฐ๐—ฒ๐˜€ ๐—ถ๐—บ๐—ฝ๐—ฎ๐—ฐ๐˜ ๐˜๐—ต๐—ฒ ๐—ณ๐—ถ๐—ป๐—ฑ๐—ถ๐—ป๐—ด๐˜€?
  • W๐—ต๐—ฎ๐˜ ๐—ฎ๐˜€๐˜€๐˜‚๐—บ๐—ฝ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ฎ๐—ถ๐—ฑ ๐˜ƒ๐˜€ ๐—ฑ๐—ถ๐˜€๐˜๐—ผ๐—ฟ๐˜ ๐˜๐—ต๐—ฒ ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น?
  • W๐—ต๐—ถ๐—ฐ๐—ต ๐—ฑ๐—ผ๐—ผ๐—ฟ๐˜€ (๐—ฎ๐—น๐˜๐—ฒ๐—ฟ๐—ป๐—ฎ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—ฎ๐—ฝ๐—ฝ๐—ฟ๐—ผ๐—ฎ๐—ฐ๐—ต๐—ฒ๐˜€) ๐—ต๐—ฎ๐˜ƒ๐—ฒ ๐˜†๐—ผ๐˜‚ ๐—ฐ๐—น๐—ผ๐˜€๐—ฒ๐—ฑ ๐—ผ๐—ป ๐˜๐—ต๐—ฒ ๐—ฟ๐—ผ๐—ฎ๐—ฑ ๐˜๐—ผ ๐˜๐—ต๐—ถ๐˜€ ๐—ผ๐—ป๐—ฒ?

And, if you like reading, pick a few books from this shelf for deeper exploration.