Nkeji

1. Ọgụgụ isi Artificial na Econometrics na Statistics: Ọrụ, Oke, Nyocha na Nzuzo 2. Nhicha na Nkwadebe Data: Data efu, Outliers, and Codeing 3. Nyocha data nyocha na nhụhụhụhụhụhụhụhụhụhụhụ anya: eserese na nkọwa ya na ọgụgụ isi nka 4. Nkwụghachi azụ Linear: Ụlọ ihe nlere anya, nkọwa nkọwa na echiche 5. Nchọpụta nyocha na mmebi iwu: Collinearity, Heteroscedasticity, Autocorrelation 6. Nnwale hypothesis na p-uru: uru, ike, na ọtụtụ atụnyere 7. p-hacking, HARKing na Statistical iguzosi ike n'ezi ihe: Ọnyà dị na Age nke ọgụgụ isi 8. Nyocha usoro oge: ọdụ, ARIMA na amụma 9. Ihe kpatara na nyocha amụma: DID, IV, RDD na ọgụgụ isi 10. Usoro Ọgbọ na Mmegharị: R/Python, Versioning na Reproducibility 11. Akuko Ide, Nkwukọrịta, na ụkpụrụ omume: Ngosipụta Nsonaazụ yana oke ịkparịta ụka

Nkeji 10 / 11

Usoro Ọgbọ na Mmegharị: R/Python, Versioning na Reproducibility

Uru:

Ikike iji nyochaa site n'ịgụ na ịnwale koodu nyocha R/Python nke ọgụgụ isi na-emepụta ma guzobe ọrụ nwere ike imepụtaghachi ya na mkpụrụ, mkpọchi ụdị na nhazi nchekwa.
Ikike iji njikwa ụdị (Git), mmemme mmuta (R Markdown / Quarto / Jupyter) na njikwa gburugburu ebe obibi na nkwado ọgụgụ isi, na-eme nyochagharị site na mmalite ruo n'isi.
Ikike ịme nnwale otu yana ịlele ịdị ọcha iji nweta mmejọ nkịtị na koodu AI (misjoin, leak, filter efu)

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