COURSE UNIT TITLE

: BIOMETRICAL ANALYSES IN AQUATIC ECOSYSTEMS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CDK 6002 BIOMETRICAL ANALYSES IN AQUATIC ECOSYSTEMS 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

MARINE LIVING RESOURCES
MARINE LIVING RESOURCES

Course Objective

This course aims to provide students a versatile understanding of sampling design and strategies for biological research and experiments at aquatic ecosystems. The theoretical and practical aspects of statistical analyses and interpretations of the results of the tests are reviewed and discussed. Measurement of species richness, diversity and evenness in aquatic ecosystems are also covered.

Learning Outcomes of the Course Unit

1   Recognize the diversity and richness of biological and environmental data in aquatic ecosystems.
2   Recognize the need for sampling design and statistical analysis in research in aquatic ecosystems.
3   Demonstrate an ability to formulate statistical hypotheses and design basic experiments or research surveys.
4   Be able to collect biological and environmental data and make them ready for statistical analysis.
5   Compute all basic statistics to describe and summarize the collected data and prepare graphics visualizing the information contained by the data.
6   Apply univariate and multivariate statistical analysis methods to make inferences about the collected data and draw meaningful and valid conclusions.
7   Demonstrate critical thinking skills in evaluation of their own research work and/or that of other researchers from a statistical point of view.
8   Demonstrate an ability to interpret, discuss and publish the results from own research work.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction Course outline, textbooks and reference books. General review of the topics to be covered in the course. Some important definitions.
2 Sampling Sampling methods. Sampling design.
3 Experimental design Design of laboratory experiments. Design of field experiments.
4 Evaluation of findings - I Descriptive statistics. Probability. Continuous probability distributions.
5 Evaluation of findings - II Discrete probability distributions. Confidence intervals. Testing of statistical hypothesis.
6 Evaluation of findings - III Visual presentations. Graphics.
7 Midterm exam
8 Comparison of two samples - I Paired (Dependent) t-test. Independent t-test. Power of tests and size of the sample.
9 Comparison of two samples - II Wald-Wolfowitz test. Mann-Whitney U test. Kolmogorov-Smirnov test.
10 Comparison of multiple samples ANOVA and MANOVA.
11 Functional relationships Simple linear regression. Correlation.
12 Data transformations Transformations of ecological data. Types of data transformation.
13 Community analysis - I Species richness. Diversity indices. Evenness indices.
14 Community analysis - II Computer programs (software) used for community analysis.

Recomended or Required Reading

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

Bakus, G. J. 2007. Quantitative Analysis of Marine Biological Communities: Field Biology and Environment. John Wiley & Sons, New Jersey, USA.
Koray, T. 1993. Su Ürünleri Araştırmalarında Biyometrik Yöntemler. Ege Üniversitesi Basımevi, Bornova, Izmir.

Reference Books:

Krebs, Charles J. 1998. Ecological Methodology. Addison-Welsey Educational Publishers Inc., California, 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

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 the examples will be chosen in a way to resemble statistical problems that students might face in preparation of a master's or doctoral thesis. Individual participation by students in classroom discussion will be strongly encouraged.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 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

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

Regular participation in classes is essential. Students are responsible for the topics covered, the assignments, changes in assignments or other verbal information given in the class, whether in attendance or not.

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 13 2 26
Preparations before/after weekly lectures 12 4 48
Reading 12 5 60
Preparation for midterm exam 1 8 8
Preparation for final exam 1 15 15
Midterm 1 2 2
Final 1 4 4
TOTAL WORKLOAD (hours) 163

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6
LO.1555255
LO.2555555
LO.3555555
LO.4554555
LO.5555555
LO.6554555
LO.7455555
LO.8455555

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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