COURSE UNIT TITLE

: APPLIED STATISTICAL METHODS IN OCEANOGRAPHY

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
COE 5039 APPLIED STATISTICAL METHODS IN OCEANOGRAPHY ELECTIVE 2 0 0 7

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

COASTAL ENGINEERING
COASTAL ENGINEERING

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

1   Recognize the need for sampling design and statistical analysis in oceanographic research.
2   Demonstrate an ability to formulate statistical and research hypotheses and design oceanographic experiments or research surveys.
3   Be able to collect raw oceanographic data and make them ready for statistical analyses.
4   Compute all statistics to describe and summarize the collected data and prepare various complicated graphics visualizing the information contained by the data.
5   Apply univariate and multivariate statistical analysis methods to make inferences about the collected data and draw meaningful and valid conclusions.
6   Become able to use certain statistical software (R Project for Statistical Computing and CANOCO) to analyse data and interpret results.
7   Demonstrate critical thinking skills in evaluation of the strengths and weaknesses of their own research work and/or that of other researchers.
8   Interpret and discuss results from research projects and communicate with others in written and verbal forms.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Course Course Outline, Textbooks, Reference books and Homework. General Review of the Structure and Collection of Oceanographic Data.
2 Statistical Programme Packages Introduction to R and CANOCO. Statistical Modules in CANOCO. Data Import and Export. Case Study: Biological Oceanographic Data.
3 Review of Relevant Statistical Methods Review and Applications of the Various Basic Oceanographic Data Analysis Methods (Simple linear regression and ANOVA). Statistical Analysis of Physical Oceanographic Data.
4 Multiple Linear Regression Multiple Linear Regression Model. Selection of Independent Variables. Dummy Variables. Regression Diagnostics.
5 Factorial Analysis of Variance Three-way ANOVA. Multi-way ANOVA. Mixed Models.
6 Nonparametric Methods Choice between Parametric and Nonparametric Methods. Wald-Wolfowitz Runs Test. Mann-Whitney U Test. Kolmogorov-Smirnov Two-Sample Test. Kruskal-Wallis ANOVA. Wilcoxon Signed-Rank Test. Sign Test. Spearman R and Kendall Tau.
7 Analysis of Frequencies (I) Tests for Goodness of Fit. Single Classification Goodness of Fit. Repeated Tests for Goodness of Fit. Test of Independence. Analysis of Two-Way Tables. Analysis of Proportions.
8 Analysis of Frequencies (II) Analysis Three- and Multi-Way Tables. Log-Linear Models.
9 Midterm Exam
10 Nonlinear Models (I) Nonlinear Regression Model. Fitting Nonlinear Regressions. Error Structure. Case Study: Chemical Oceanographic Data Analysis.
11 Nonlinear Models (II) Asymptotic Regression. Logistic Regression. Probit Regression. Case Study: Biological Oceanographic Data Analysis.
12 Multivariate Methods (I) Multivariate Oceanographic Data. Multivariate Normal Distribution. Review of Some Matrix Algebra. Multivariate Analysis of Variance. Case Study: Marine Geological Data Analysis.
13 Multivariate Methods (II) Multivariate Distances. Principal Component Analysis. Factor Analysis. Cluster Analysis. Ordination. Correspondence Analysis.
14 Midterm Exam

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

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG 1 ASSIGNMENT 1
2 ASG 2 ASSIGNMENT 2
3 MTE MIDTERM EXAM
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE ASG 1 * 0.10 + ASG 2 * 0.10 + MTE * 0.20 + FIN *0.60
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) ASG 1 * 0.10 + ASG 2 * 0.10 + MTE * 0.20 + RST *0.60


Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

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

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 2 24
Preparation for midterm exam 2 8 16
Preparation for final exam 1 14 14
Preparations before/after weekly lectures 11 5 55
Preparing assignments 10 5 50
Midterm 2 2 4
Final 1 4 4
TOTAL WORKLOAD (hours) 167

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.13341311312
LO.23341211213
LO.33421211211
LO.44531211312
LO.55424112213
LO.65311121222
LO.75341111224
LO.85341212211

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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