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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS LGM 2003 STATISTICS FOR BUSINESS AND MANAGEMENT COMPULSORY 3 0 0 6

Offered By

Logistics Management (English)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR IDIL YAVUZ

Offered to

Logistics Management (English)

Course Objective

To teach basic statistical concepts and how statistics can be used in management via performing data analysis and various applications in SPSS.

Learning Outcomes of the Course Unit

1   Being able to define fundamental concepts in statistics, performing descriptive analysis and preparing graphical displays of data 2   Being able to calculate probability using basic rules of probability and probability distributions 3   Performing hypothesis testing 4   Building and interpreting simple and multiple regression models 5   Forecasting future values of a random variable using time series analysis 6   Applying statistical analysis in SPSS

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Fundamental concepts in statistics and graphical displays 2 Descriptive statistics 3 Fundamental concepts in probability 4 Discrete probability distributions 5 Continuous probability distributions 6 Fundamentals of hypothesis testing 7 One sample hypothesis testing 8 Two sample hypothesis testing 9 Simple linear regression 10 Multiple linear regression 11 Fundamentals of time series analysis 12 Exponential smoothing method 13 Applications in SPSS 14 Applications in SPSS

Recomended or Required Reading

Newbold, P., Carlson W.L., Thorne B.M., Statistics for Business and Economics, Pearson. McClave, J., Benson, P.G, Sincich, T., Statistics for Business and Economics, Pearson. Goodwin E.M., Kemp, J. Marine Statistics Theory and Practice, Stanford Maritime.

Planned Learning Activities and Teaching Methods

Lectures, case studies

Assessment Methods

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

Further Notes About Assessment Methods

None

Assessment Criteria

Midterm and final (make-up) tests

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

idil.yavuz@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparations before/after weekly lectures 14 2 28 Preparation for midterm exam 1 30 30 Preparation for final exam 1 35 35 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 139

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 PO.11 PO.12 PO.13 LO.1 3 3 3 3 3 3 3 LO.2 3 3 3 3 3 3 3 3 3 LO.3 3 3 3 3 3 3 3 3 3 3 LO.4 3 3 3 3 3 3 3 LO.5 3 3 3 3 3 3 3 3 3 3 3 LO.6 3 3 3 3 3 3 3 3 3 3 3 3 3