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  Course Description
Course Name : STATISTICAL ESTIMATION METHODS FOR FISHERIES

Course Code : ST-506

Course Type : Optional

Level of Course : Second Cycle

Year of Study : 1

Course Semester : Spring (16 Weeks)

ECTS : 6

Name of Lecturer(s) : Prof.Dr. MUSTAFA AKAR

Learning Outcomes of the Course : Understands the purpose and importance of making estimations for fisheries
Knows about the least squares method and maximum likelihood method
Understands the properties of estimates (impartiality, competence, effectiveness and coherence)
Learns and understands the topics such as hypothesis testing, confidence intervals estimation

Mode of Delivery : Face-to-Face

Prerequisites and Co-Prerequisites : None

Recommended Optional Programme Components : None

Aim(s) of Course : To teach the statistical estimation methods that is important for fisheries studies

Course Contents : Goal and importance of statistical estimation for fisheries; point estimations (method of moments, least squares method and maximum likelihood method); properties of estimators (unbiased, sufficiency, efficiency and consistency); interval estimation; hypothesis testing, likelihood ratio test; maximum likelihood method for multivariate case

Language of Instruction : Turkish

Work Place : Classrooms of Fisheries Faculty


  Course Outline /Schedule (Weekly) Planned Learning Activities
Week Subject Student's Preliminary Work Learning Activities and Teaching Methods
1 Goal and importance of statistical estimation for fisheries; Related sources reading Visual and oral presentation
2 Point estimations Related resources reading Visual and oral presentation
3 Point estimations Related resources reading Visual and oral presentation
4 Least Square Methods Related resources reading Visual and oral presentation
5 Maximum likelihood method Related resources reading Visual and oral presentation
6 Properties of estimators (unbiased, sufficiency, efficiency and consistency); Related resources reading Visual and oral presentation
7 Interval estimation Related resources reading Visual and oral presentation
8 Mid-term exam Written exam
9 Hypothesis testing Related resources reading Visual and oral presentation
10 Hypothesis testing Related resources reading Visual and oral presentation
11 Maximum likelihood ratio test Related resources reading Visual and oral presentation
12 Maximum likelihood ratio test Related resources reading Visual and oral presentation
13 Maximum likelihood ratio test Related resources reading Visual and oral presentation
14 Maximum likelihood method for multivariate case Related resources reading Visual and oral presentation
15 Maximum likelihood method for multivariate case Related resources reading Visual and oral presentation
16/17 Final exam Written Exam


  Required Course Resources
Resource Type Resource Name
Recommended Course Material(s)  Morris H. deGroot 1986, Probability and Statistics. Addison-Wesley publishing Company, London
 Paul G. Hoel 1971, Introdusction to mathematical statistics. Wiley international edition. London
Required Course Material(s)


  Assessment Methods and Assessment Criteria
Semester/Year Assessments Number Contribution Percentage
    Mid-term Exams (Written, Oral, etc.) 1 70
    Homeworks/Projects/Others 10 30
Total 100
Rate of Semester/Year Assessments to Success 40
 
Final Assessments 100
Rate of Final Assessments to Success 60
Total 100

  Contribution of the Course to Key Learning Outcomes
# Key Learning Outcome Contribution*
1 Improves theoretical and practical knowledge in the field of Marine and Inland Water Biology and Fisheries Basic Sciences. 4
2 Comprehends interactions between Fisheries Basic Sciences and other disciplines. 4
3 Determines strategies and investigates methods about their field of study in Fisheries Basic Science. 4
4 Produces new information and theories by interpreting and synthesising the information from other disciplines and uses the theoretical and practical information from their field of study in Fisheries Basic Science. 4
5 Collects data, interprets results and suggests solutions by using dialectic research methodology in the certain field of Marine and Inland Water Biology and Fisheries Basic Sciences. 4
6 Independently plans, designs and performs a certain project in the field of Fisheries Basic Sciences. 4
7 Produces solutions by improving new strategic approaches and taking responsibilities for the potential problems in the field of study as an individual or team member. 4
8 Determines the requirements for Fishery Basic Science education, reaches the resources, critically interpretes knowledge and skills and gains experience to direct the education. 4
9 Has positive stance on the lifelong education and uses it for the public benefit by using the gained theoretical and practical knowledge in the field of Marine and Inland Water Biology and Fisheries Basic Sciences. 4
10 Follows the current topics and improvements in the field of Fisheries Basic Sciences, publishes and presents the research results, contributes to constitution of a public conscience in the field of interest. 4
11 Effectively communicates about the field of Marine and Inland Water Biology and Fisheries Basic Sciences by using written and oral presentation tools, follows up and criticizes the meetings and seminars. 4
12 Follows up international publications and communicates with international collaborators by using language skills. 4
13 Uses the communication and information technologies about the field of interest in an advanced level. 4
14 Conforms, controls and teaches social, cultural and scientific ethics in the investigation and publication process of the data related with the field of interest. 4
15 Improves strategies, politics and application codes by following scientific and technological developments on the certain field of Marine and Inland Water Biology and Fisheries Basic Sciences. Investigates and extends the results on behalf of public in frame of total quality management process. 4
16 Uses the abilities and experiences on applications and solving problems that gained during the MSc education for the interdisciplinary studies. 4
* Contribution levels are between 0 (not) and 5 (maximum).

  Student Workload - ECTS
Works Number Time (Hour) Total Workload (Hour)
Course Related Works
    Class Time (Exam weeks are excluded) 14 4 56
    Out of Class Study (Preliminary Work, Practice) 14 4 56
Assesment Related Works
    Homeworks, Projects, Others 10 3 30
    Mid-term Exams (Written, Oral, etc.) 1 3 3
    Final Exam 1 3 3
Total Workload: 148
Total Workload / 25 (h): 5.92
ECTS Credit: 6