Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
9104035502011Statistical Analysis and their Interpretations in Aquatic Sciences II Elective128
Level of Course Unit
Second Cycle
Objectives of the Course
The aim of this course, the license was seen using the statistical program SPSS course, non-parametric and multivariate statistical techniques to help implement and interpret the results.
Name of Lecturer(s)
Doç. Dr. Hülya SAYĞI
Learning Outcomes
1How to gather statistical data,
2Use of sampling methods,
3The data obtained will have general information on how to understand,
4Outlier in the data to test whether the data,
5Which is non-parametric tests,
6Measurements of fish in aquaculture is to reveal the relationship.
Mode of Delivery
Face to Face
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
How to obtain the data sampling method in fisheries studies, the data from the non-parametric and multivariate statistical analysis using SPSS to analyze and interpret.
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
1Introduction to methods of statistical analysis, the data is there and how many types of data, data collection, the frequency table of thecreation, discovery of outlier data.In fisheries studies in the statistical analysis
2Sampling and sampling methods, sampling methods used in thestudy sample size calculation in FisheriesExamination of sampling methods used in Fisheries
3SPSS program to edit and display the dataSPSS program to edit and display the data
4Descriptive statistics are used in fisheriesExamination of examples of the descriptive statistics by SPSS
5Nonparametric hypothesis testingChi-square test, Runs test, Mann-Whitney U test, Wilcoxon sign test, Kruskal-Wallis test, concerning the application made by SPSS
6Nonparametric hypothesis testingtest, Mann-Whitney U test, Wilcoxon sign test, Kruskal-Wallis test, concerning the application made by SPSS
7MID-TERM EXAM
8Introduction to multivariate statistical techniquesMultivariate statistical tests to determine by SPSS, the preparation of term papers
9Analysis of varianceAnalysis of variance on the examination of MANOVA'nın examples,the duty of the preparation period
10Analysis of covarianceANCOVA analysis on the samples, the preparation of term papers
11Logistic and probit regression modelLogit and probit models are obtained by the SPSS, the preparation of term papers
12Survival AnalysisSurvival Analysis by the SPSS, the preparation of term papers
13Term Paper PresentationsTerm Paper Presentations
14Term Paper PresentationsTerm Paper Presentations
15Term Paper PresentationsTerm Paper Presentations
16Term Paper PresentationsTerm Paper Presentations
Recommended or Required Reading
Alpar, R., 2003, Uygulamalı Çok Değişkenli İstatistiksel Yöntemlere Giriş 1, 2. Baskı, 411s. Elbek, A.G., Oktay, E., ve Saygı, H., 2008, Su Ürünlerinde Temel İstatistik, Ege Üniveristesi, Su Ürünleri Fakültesi Yayınları, Su Ürünleri Fakültesi Yayın No: 19, Ders Kitabı Dizin No: 6, 6. Baskı, 297s. Kalaycı, Ş., 2008, SPSS, Uygulamalı Çok Değişkenli İstatistik Teknikleri, Asil Yayın Dağıtım Ltd. Şti, Ankara. Özdamar, K.,1999, SPSS ile Biyoistatistik, Kaan Kitapevi, 3. Baskı, 454s. Sümbüloğlu, K. ve Sümbüloğlu, V., 2005, Biyoistatistik, Hatipoğlu Yayınları, 11. baskı, 270s.
Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
SUM0
End Of Term (or Year) Learning ActivitiesQuantityWeight
SUM0
SUM0
Language of Instruction
Turkish
Work Placement(s)
None
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
Midterm Examination133
Final Examination133
Report Preparation19090
Report Presentation111
Criticising Paper10220
Individual Study for Mid term Examination15345
Individual Study for Final Examination15345
Reading16232
TOTAL WORKLOAD (hours)239
Contribution of Learning Outcomes to Programme Outcomes
PO
1
PO
2
PO
3
PO
4
PO
5
PO
6
PO
7
LO15555  5
LO2555   5
LO35555 55
LO45 55  5
LO55  5  5
LO655555 5
* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High
 
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