• 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 5063 SAMPLING THEORY ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ISTEM KÖYMEN

Offered to

Econometrics

Course Objective

Social science data collection, classification, data collection methods, identification, according to the methods of data collection to obtain the estimates, sampling methods and estimates to compare the effectiveness and the use of estimates in accordance with data found.

Learning Outcomes of the Course Unit

1   Defining feature of the population may represent an example of 2   Statistics properties of a representative sample of the population at each sampling method 3   Choosing correct sampling methods depends on population circumstances 4   Representative of the population at each sampling method to calculate the sample statistics 5   Statistics to determine the properties of the sample is obtained. 6   Sampling methods comparable activities.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Steps of sampling, relationship between samping theory and statistical theory 2 Simple random sampling, replacement and without replacement sampling, point estimation and interval estimation 3 Mean, total and ratio estimates and obtain their statistical in simple random sapmling 4 Replacement and without replacement sampling in stratified sampling, point and interval estimation 5 Mean, total and ratio estimates in stratified sampling 6 The methods used in determining the sample size; equal allocation, proportional allocation, optimum allocation, Neyman allocation and comparison of methods 7 Replacement and without replacement sampling in cluster sampling, point and interval estimation 8 Mid-term 9 Mean, total and ratio estimates in cluster sampling, Two and implementation of a multi-stage cluster sampling 10 Mean, total and ratio estimates in systematic sampling 11 Stratified systematic sampling 12 Sampling linear trend populations, sampling periodic trend populations 13 Comparison of the effects of sampling methods 14 Applications

Recomended or Required Reading

Sampling Techniques, William G. Cochran

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 * 0.30 + STT * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40

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 2 26 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) 131

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 1 1 LO.3 1 1 1 LO.4 1 1 1 LO.5 1 1 1 LO.6 1 1 1