ST0032 Statistical analysis for fisheries sciences-II

6 ECTS - 4-2 Duration (T+A)- . Semester- 5 National Credit

Information

Code ST0032
Name Statistical analysis for fisheries sciences-II
Semester . Semester
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 Goal

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 Improves theoretical and practical knowledge in the field of Marine and Inland Water Biology and Fisheries Basic Sciences. 5
PLO02 Bilgi - Kuramsal, Olgusal Comprehends interactions between Fisheries Basic Sciences and other disciplines. 4
PLO03 Bilgi - Kuramsal, Olgusal Determines strategies and investigates methods about their field of study in Fisheries Basic Science. 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