• 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 ERA 1401 STATISTICS I ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

Offered to

Econometrics (Evening) Econometrics

Course Objective

The main objective of the course is to give the student an elementary introduction to the practice of statistics. This course will give insight into how an analyst gathers, summarizes, and draws conclusions from economical or business data. At the end of the course, the student should be a critical consumer of this information.

Learning Outcomes of the Course Unit

1   To be able to understand the relation of science and statistics 2   To be able to use measures of central tendency and variation 3   To be able to present frequencies with graphs 4   To be able to classify variables with regard to their features 5   To be able to identify the shape of the distribution by using the measures of central tendency 6   To be able to define the basic concepts of statistics 7   To be able to show the relations between distributions

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

HAZIRLIK - FOREIGN LANGUAGE PREPARATION CLASS

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to statistics, basic concepts, statistic, population, parameter, variable, data 2 Gathering data, classifying, graphical representations, frequency distributions, pie nd bar charts, time series charts, scatter diagrams, histograms, frequency poligons 3 Measures of central tendency: mean, mode, median, geometric mean, harmonic mean, quartiles. 4 Measures of variation and asymmetry: range, Standard deviation, variance, absolute deviation, men absolute deviation. 5 Bowley and pearson asymmetry measures. 6 Permutation, combination 7 Probability theorems, dependent/independent events, conditional probability, Bayes Theorem, discrete/continuous random variable, probability density function, expected value, moments. 8 Mid-term 9 Mid-term 10 Discrete probability distributions 11 Normal Distribution 12 Central Limit Theorem 13 Sampling distributions 14 Properties of estimators

Recomended or Required Reading

Statistics for Business and Economics, Paul Newbol

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 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Mid-term exam :40% Final-exam : 60%

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Doç. Dr. Kadir ERTAŞ: kadir.ertas@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 3 36 Preparation for midterm exam 1 20 20 Preparation for final exam 1 25 25 Preparations before/after weekly lectures 12 3 36 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 119

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 LO.4 1 LO.5 1 LO.6 1 LO.7 1