• HOME
• ABOUT US
  • Name Address
  • General Description
  • Governance
  • Academic Calendar
  • Degree Programmes
  • List of Programmes in English
  • General Admission and Registration Procedures
  • Credit Mobility and Recognition of Prior Learning
  • ECTS Credit Allocation
  • Academic Guidance
  • Contacts
• Degree Programmes
  • Third Cycle Programmes (Doctorate Degree)
  • Second Cycle Programmes (Master's Degree)
  • First Cycle Programmes (Bachelor's Degree)
  • Short Cycle Programmes (Associate's Degree)
• GENERAL INFORMATION FOR STUDENTS
  • Cost of Living
  • Accommodation
  • Meals
  • Medical Facilities
  • Facilities for Disabled Students
  • Insurance
  • Financial Supports
  • Student Affairs Office
  • Practical Information for International Students
  • Language Courses
  • Work Placement Possibilities
  • Sports, Social and Cultural Facilities
  • Student Associations and Clubs
  • About İzmir - Turkey
• INTERNATIONAL RELATIONS
  • International Relations Office
  • Registration Procedures
  • Agreements
  • Coordinators
  • Documents
  • List of Programmes in English
  • ECTS / DS Labels

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 5032 STATISTICAL INFERENCE COMPULSORY 3 0 0 6

Offered By

Econometrics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR KADIR ERTAŞ

Offered to

Econometrics

Course Objective

Understand the statistical estimation theory to provide a theoretical properties of point and interval estimation and statistical theory explaining the infrastructure to gain.

Learning Outcomes of the Course Unit

1   To be able to apply the central limit theorem 2   To be able to obtain parameter of discrete and continuous distributions using the maximum likelihood method. 3   Belli varsayımlar altında populasyon parametreleri için aralık tahminlemesi yapabilme. 4   Belli varsayımlar altında populasyon parametreleri için hipotez testleri yapabilme.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Proof of the Central Limit Theorem and Applications 2 Distribution of Sample Mean for finite populations 3 Theorems about the independence of the mean and variance of random examples 4 Point estimators and point estimators features 5 Cramer-Rao inequality and related problems 6 Continuous Uniform, Exponential, Gamma and Normal Distribution s estimators and applications 7 Definition of Maximum Likelihood Method and Mathematical Structure 8 Midterm 9 Application of Maximum Likelihood Estimation on Binomial and Normal distribution 10 Theory of Confidence Intervals 11 Applications of Confidence Intervals 12 Statistical Hypothesis Testing Theory 13 Applications of Statistical Hypothesis Testing 14 Article discussions

Recomended or Required Reading

1- Mathematical Statistics, Prentice Hall, Freund, J.E. 2- Introduction to the Theory of Statistics, McGraw-Hill Book, Mood, A.M., Graybill, F.A.

Planned Learning Activities and Teaching Methods

Discussing, Problem solving, Lecture Method, Question-Answer Method

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 STT TERM WORK (SEMESTER) 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.25 + STT * 0.25 + FIN* 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE* 0.25 + STT * 0.25 + RST* 0.50 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

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)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 3 39 Preparation for midterm exam 1 30 30 Preparation for final exam 1 30 30 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 144

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 LO.1 1 1 1 LO.2 1 LO.3 1 LO.4 1