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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EMT 2008 MATHEMATICAL STATISTICS II COMPULSORY 3 0 0 4

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

Offered to

Econometrics (Evening) Econometrics

Course Objective

Statistics by emphasizing the direction of mathematical science, forecasting and statistical decision-making (hypothesis testing) to teach the theory.

Learning Outcomes of the Course Unit

1   To be able to examine properties of estimators 2   To be able to estimate the population parameters with moments method 3   To be able to estimate the population parameters with maximum likelihoods methods 4   To be able to make the use of theoritical approaches for estimators in econometrics, economics, operations methods and business administration 5   To be able to make the use of theoritical approaches for hypothesis in econometrics, economics, operations methods and business administration

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Central Limit Theorem; Basic consepts for statistical inference 2 The basic consepts of estimators; properties of point estimators: unbiasedness, consistency 3 Properties of point estimators continued: sufficiency, efficiency 4 The method of moments in estimation 5 The maximum likelihood methods in estimation 6 Moments estimators for the well known discrete and continuous distributions 7 Moments estimators for the well known discrete and continuous distributions continued 8 Mid-term 9 Mid-term 10 Maximum likelihood estimators for the well known discrete and continuous distributions 11 Maximum likelihood estimators for the well known discrete and continuous distributions continued 12 Comparisions of moments method and maximum likelihood methods 13 Hypothesis Testing Theory 14 Calculation of power of test

Recomended or Required Reading

1- Miller I., Miller M., John E. Freund's Mathematical Statistics, Sixth Edition, New Jersey 2- Hogg R V & Craig A T, Introduction to Mathematical Statistics, 4th Ed, Macmillan, London 3-Ross S M, A First Course in Probability, Academic Press, NY

Planned Learning Activities and Teaching Methods

This course will be presented using class lectures, class discussions, overhead projections, and demonstrations.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 MTEG MIDTERM GRADE MTEG * 1 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Doç.Dr. Kadir ERTAŞ e-mail: kadir.ertas@deu.edu.tr Room: 634 Tel : 0 (232) 301 03 66 Int: 10366

Office Hours

Thursday: 16:00 - 18:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 3 36 Preparations before/after weekly lectures 12 2 24 Preparation for midterm exam 1 20 20 Preparation for final exam 1 28 28 Midterm 1 1 1 Final 1 1 1 TOTAL WORKLOAD (hours) 110

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 1 LO.2 1 LO.3 1 1 LO.4 1 LO.5 1