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 9 / 11

Ihe kpatara na nyocha amụma: DID, IV, RDD na ọgụgụ isi

Uru:

Ịghọta ọdịiche dị n'etiti mmekọrịta na ihe kpatara ya na mgbagha nke atụmatụ dị ka ọdịiche-in-iche (DiD), ngwá ọrụ mgbanwe (IV), nkwụsịtụ nkwụsị (RDD) na nkwado nke ọgụgụ isi artificial.
Inwe ike ịhụ nkọwa nkọwa nke atụmatụ nke ọ bụla dabere (usoro ndị yiri ya, mmachi mwepu, ịga n'ihu na nkwụsị) yana ọrụ AI na-emepụta koodu ule / nchekwa.
Ikike iji nyochaa nke ọma atụmatụ nke ịmata na ịchọpụta nkọwa nke ọgụgụ isi na-emepụta ihe na-ebute oke ihe kpatara site na data nlele.

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