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Information
| Code | ST0032 |
| Name | Statistical analysis for fisheries sciences-II |
| Term | 2024-2025 Academic Year |
| Term | Spring |
| Duration (T+A) | 4-2 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 5 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | |
| Course Instructor |
1 |
Course Goal / Objective
The aim of this course is to teach students how to do statistical analysis of data by using computer programs (SPSS/R/Tableau/EXCEL) and how to interpret and visualize the results.
Course Content
Data preperation. Ecological index and abundance/biomass comparisons. Assumption checking on multivariate statistical techniques. Canonical correlation analysis. Multiple linear regression analysis. Logistic regression analysis. Principal component analysis. Factor analysis. Confirmatory factor analysis. Multidimentional scaling. Reliability analysis.
Course Precondition
To have taken the Statistical Analysis Methods in Fisheries-I course or another course that overlaps with the contents of the relevant course.
Resources
Crawley, M. J. (2012). The R book. John Wiley & Sons Karagör Y. (2018). SPSS/AMOS 23 ile Uygulamalı istatistiksel analizler. Nobel Yayınevi Clarke, K.R., Warwick, R.M., 2001. Change in marine communities: an approach to statistical analysis and interpretation,. 2nd edition. PRIMER-E: Plymouth
Notes
Kalaycı, Ş. (2010). SPSS uygulamalı çok değişkenli istatistik teknikleri (Vol. 5). Ankara, Turkey: Asil Yayın Dağıtım.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | With this course, students will have the ability to analyze the data obtained from both the real environment and the experimental studies. |
| LO02 | Learns how to prepare the data at hand for analysis before analysis |
| LO03 | Learns how to visualize analysis results. |
| LO04 | Gains general knowledge of some of the commonly used statistical package programs. |
| LO05 | Gains the ability to interpret the outputs obtained from statistical package programs |
| LO06 | Gains the ability to construct the relationship between different disciplines statistically |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Develops theoretical and practical knowledge in the field of Marine Biology, Inland Water Biology or Basic Sciences in Fisheries at the level of expertise. | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Comprehends interactions between Fisheries Basic Sciences and other disciplines. | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Determines the strategies related to the field of specialization in Basic Sciences of Aquaculture; explains the methods and techniques, measurement and concepts. | 5 |
| PLO04 | Bilgi - Kuramsal, Olgusal | 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. | 5 |
| PLO05 | Bilgi - Kuramsal, Olgusal | 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. | 5 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Independently plans, designs and performs a certain project in the field of Fisheries Basic Sciences. | 4 |
| PLO07 | Bilgi - Kuramsal, Olgusal | 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. | 3 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Determines the requirements for Fishery Basic Science education, reaches the resources, critically interpretes knowledge and skills and gains experience to direct the education. | 3 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | 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. | |
| PLO10 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | 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. | |
| PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | 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. | |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Follows up international publications and communicates with international collaborators by using language skills. | |
| PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Uses the communication and information technologies about the field of interest in an advanced level. | 3 |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | Conforms, controls and teaches social, cultural and scientific ethics in the investigation and publication process of the data related with the field of interest. | 5 |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | 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. | |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Uses the abilities and experiences on applications and solving problems that gained during the MSc education for the interdisciplinary studies. | 5 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Data preperation | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Anlatım |
| 2 | Data preperation in R/SPSS | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Anlatım |
| 3 | Ecological index and abundance/biomass comparisons | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösterip Yaptırma |
| 4 | Ecological index and abundance/biomass comparisons in R | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 5 | Assumption checking on multivariate statistical techniques | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 6 | Assumption checking on multivariate statistical techniques in R/SPSS | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 7 | Multiple linear regression analysis and its application in SPSS | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösterip Yaptırma |
| 8 | Mid-Term Exam | Reading of notes taken from previous courses | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Canonical correlation analysis in R/SPSS | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösterip Yaptırma |
| 10 | Logistic regression analysisin R/SPSS | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösterip Yaptırma |
| 11 | Principal component analysis in R/SPSS | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösterip Yaptırma |
| 12 | Factor analysis in SPSS | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösterip Yaptırma |
| 13 | Confirmatory factor analysis in SPSS/AMOS | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösterip Yaptırma |
| 14 | Multidimentional scaling in R | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösterip Yaptırma |
| 15 | Reliability analysis in SPSS | The relevant topic is read from the lecture notes. | Öğretim Yöntemleri: Alıştırma ve Uygulama, Gösterip Yaptırma |
| 16 | Term Exams | Reading of notes taken from previous courses | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
| 17 | Term Exams | Reading of notes taken from previous courses | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 4 | 56 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 6 | 6 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 150 | ||
| Total Workload / 25 (h) | 6,00 | ||
| ECTS | 6 ECTS | ||