Keywords: Best Linear Approximation (1)

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Statistical Method in Economics, Fall 2006

Statistical Method in Economics, Fall 2006

The course introduces statistical theory to prepare students for the remainder of ... (more)

The course introduces statistical theory to prepare students for the remainder of the econometrics sequence. The emphasis of the course is to understand the basic principles of statistical theory. A brief review of probability will be given; however, this material is assumed knowledge. The course also covers basic regression analysis. Topics covered include probability, random samples, asymptotic methods, point estimation, evaluation of estimators, Cramer-Rao theorem, hypothesis tests, Neyman Pearson lemma, Likelihood Ratio test, interval estimation, best linear predictor, best linear approximation, conditional expectation function, building functional forms, regression algebra, Gauss-Markov optimality, finite-sample inference, consistency, asymptotic normality, heteroscedasticity, and autocorrelation. (less)

Subject:
Mathematics and Statistics
Social Sciences
Material Type:
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Chernozhukov, Victor
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2002 llaF ,gnivloS melborP gnireenignE dna sretupmoC ot noitcudortnI

.desu si egaugnal gnimmargorp avaJ ehT .gninnalp dna ,tnemeganam ,ecneics ,gnireenigne ni ... (more)

.desu si egaugnal gnimmargorp avaJ ehT .gninnalp dna ,tnemeganam ,ecneics ,gnireenigne ni smelborp gnivlos rof seuqinhcet gnipoleved no si sisahpmE .scipot decnavda detceles dna scihparg retupmoc ,gnihcraes dna gnitros ,serutcurts atad ,sdohtem laciremun ,secafretni resu lacihparg ,stpecnoc gnimmargorp revoc smelborp gnimmargorp ylkeeW .esruoc eht fo sucof eht si tnempoleved dna ngised erawtfos detneiro-tcejbO .snoitacilppa cifitneics dna gnireenigne rof sdohtem lanoitatupmoc dna tnempoleved erawtfos latnemadnuf stneserp esruoc sihT (less)

Subject:
Science and Technology
Material Type:
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
George Kocur
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