COURSE UNIT TITLE

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR EYÜP MÜMTAZ TIRAŞIN

Offered to

Course Objective

The aim of the course is to teach the advanced modern data analysis tools to oceanographers via oceanographic data. The branches of oceanography (physical, chemical, biological and geological) use data sets, which are completely different in character like the disciplinary sources of the oceanographers. These advanced tools are applied for the practical use of this interdisciplinary community by using their own data sets and personal computer statistical packages (R and CANOCO).

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Recomended or Required Reading

Textbooks: (Appropriate parts of below listed books will constitute basic teaching material)

Devore, J. L., 2009. Probability and Statistics for Engineering and the Sciences (7th edition). Brooks/Cole, California, USA.
Navidi, W., 2011. Statistics for Engineers and Scientists (3rd edition). McGraw-Hill Co., New York, USA.
Thiébaux, H. J., 1994. Statistical Data Analysis for Ocean and Atmospheric Sciences. Academic Press, London, UK.

Reference Books:

Dalgaard, P., 2002. Introductory Statistics with R. Springer, New York, USA.
Snedecor, G. W. and Cochran, W. G., 1989. Statistical Methods (8th edition). Iowa State University Press. Ames, Iowa, USA.
Sokal, R. R. and Rohlf, F. J., 2012. Biometry (4th edition). W. H. Freeman Co., New York, USA.
Zar, J. H., 2010. Biostatistical Analysis (5th edition). Pearson Prentice-Hall, New Jersey, USA

Planned Learning Activities and Teaching Methods

1. Lectures
Class lectures are carried out in a highly interactive format. The instructor prompts students for response to questions posed and solicits their thoughts on issues discussed. Lectures will focus on the transfer of basic statistical concepts and techniques rather than rigorous mathematics. The emphasis will be put on the real world applications, and additional elaboration and illustration will be provided for better comprehension.
2. Class Discussions
In-class assignments and homework assignments are the basis of problems to be solved in classroom discussions. Individual participation by students in classroom discussion will be strongly encouraged.
3. Computer Applications
The R - free software environment for statistical computing and graphics (R Project for Statistical Computing) and CANOCO will be introduced to perform analyses of data and to produce graphics.
4. Calculator
Students will need a scientific calculator (preferably one that can perform basic statistical functions for both one and two variable analyses) for various calculation problems in and out of class, and during exams.

Assessment Methods

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

1. Regular attendance is essential for satisfactory completion of this course. Statistics is a cumulative subject and each lesson day builds on the previous lessons' material. If you have excessive absences, you cannot develop to your fullest potential in the course.
2. The student is responsible for all homework assignments, changes in assignments or other verbal information given in the class, whether in attendance or not.
3. Homework assignments must be delivered at the beginning of the lesson on the date they are due.
4. Students are required to have their own calculator for this course.

Contact Details for the Lecturer(s)

Dr. E. Mümtaz TIRAŞIN
Dokuz Eylül University, Institute of Marine Sciences and Technology,
Inciraltı 35340, Balçova - Izmir.
Phone:(+90) 232 2785565 /165
Fax: (+90) 232 2785082
E-mail: mumtaz.tirasin@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes