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ECON 222

Statistical Estimation and Inference

ECON 222 is where probability stops being abstract and becomes a tool for actually saying something about the world from a finite sample — how confident you can be in an estimate, when a difference is real versus noise, and how to model relationships between variables. You'll spend the semester deriving estimators and their properties, building confidence intervals and hypothesis tests for one- and two-population problems, and then pivoting into linear regression (simple and multiple), with weekly lab work in a statistical package to actually run the procedures on data. It picks up directly from ECON 221's probability foundations and is the bridge into ECON 311 econometrics — basically, this is the course that teaches you to think like an empirical economist before you're trusted with real econometric modeling.

Credit3ECTS5FacultyFaculty of Economics, Administrative, and Social SciencesBölümEconomicsPre(ECON 221 or MATH 119 or MATH 264 or PSYC 202) and (ECON 225 or MATH 227)MüfredatY2 Bahar

Değerlendirme 100% — 5 adım

20%
20%
35%
20%
5%
Midterm:Essay/written Midterm 1, Midterm 2 40%
Final:Essay/written Final 35%
Homework Homework (upto 5) 20%
Lab work Recitations (upto 10) 5%

Haftalık müfredat 14 hafta

Hafta 1
Topics of ECON 221 deferred to ECON 222 if any, Point estimators: Derivation, Properties
Hafta 2
Confidence intervals: One population
Hafta 3
Confidence intervals, Hypothesis testing: One population
Hafta 4
Hypothesis testing: One population
Hafta 5
Confidence intervals: Two populations
Hafta 6
Confidence intervals, Hypothesis testing: Two populations
Hafta 7
Hypothesis testing: Two populations
Hafta 8
Recap: Confidence intervals and Hypothesis testing
Hafta 9
Extents of Linear Regression Analysis; econometric modeling; Occam's razor and the principle of parsimony
Hafta 10
Model of mean, Simple Linear Regression (SLR) model, Multiple Linear Regression (MLR) model; functional forms and elasticity calculations
Hafta 11
Deriving the estimators of the linear regression parameters, in the model of mean, in SLR and in MLR
Hafta 12
Goodness of fit; Modeling examples
Hafta 13
Inference in Linear Regression Analysis: relating the t tests and F tests
Hafta 14
Model building, reduction and inference

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Geçmiş GPA dağılımı 45 dönem · ort. 2.18

DönemCourse CPA
2025-2026 Fall 2.89 6 sec · 97 öğr
2024-2025 Fall 2.07 6 sec · 120 öğr
2024-2025 Spring 1.97 11 sec · 249 öğr
2023-2024 Fall 2.16 6 sec · 138 öğr
2023-2024 Spring 2.05 10 sec · 213 öğr
2022-2023 Fall 1.89 6 sec · 112 öğr
2022-2023 Spring 2.27 10 sec · 208 öğr
2021-2022 Fall 2.06 5 sec · 98 öğr
2021-2022 Spring 2.28 9 sec · 179 öğr
2020-2021 Fall 2.31 6 sec · 150 öğr

Aggregate course GPA — Bilkent STARS'tan public data. Hoca-bazlı per-section detayı için STARS evaluation report →. Öğrenci anket cevapları KVKK kapsamında defter'de tutulmaz.

⚠️ FZ engelleyen şartlar

There is no compulsory or bonus-bearing attendance for any course activity other than the final exam. Failing to take the final exam returns an FX.

Hocalar 1 bu dönem · 33 geçmiş

Bu dönem (2025-2026 Spring) · 10 section
Mustafa Eray Yücel ×10
Geçmişte ders veren (33 kişi)
Tarık Kara, İnci Apaydın, Syed Fahri Mahmud, Cavit Pakel, Fatin Sezgin, Kıvılcım Metin, Pelin Kale Attar, Ashoke Kumar Sinha, Cemal Deniz Yenigün, Dilek Önkal, Defne Mutluer, Sevinç Mıhcı, Esin Celasun, Bilin Neyaptı, Ferya Kadıoğlu +18 kişi daha