SUF201 Statistics

4 ECTS - 2-2 Duration (T+A)- 3. Semester- 3 National Credit

Information

Unit FACULTY OF FISHERIES
AQUA PRODUCTS ENGINEERING PR.
Code SUF201
Name Statistics
Term 2018-2019 Academic Year
Semester 3. Semester
Duration (T+A) 2-2 (T-A) (17 Week)
ECTS 4 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Label C Compulsory
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. MAKBULE BAYLAN
Course Instructor Prof. Dr. MAKBULE BAYLAN (Güz) (A Group) (Ins. in Charge)


Course Goal / Objective

Teaching Data, Measures of Location, Distribution Measures, Probability, discrete and continuous probability functions, distributions, hypothesis testing, confidence intervals, such as regression and correlation with the basic statistical concepts and methods.

Course Content

Introduction to statistics, basic concepts and symbols, frequency distributions, measures of location (mean, weighted mean, median, mod and geometric mean), measures of dispersion (range, variance, standard error of mean, coefficient of variation), probability, discrete distributions (Binomial, Poisson), normal distribution, hypothesis testing (z- and t- tests), chi-square test, analysis of regression and correlation.

Course Precondition

Yok

Resources

Notes

Ders Notu ve KitaplarDiger Kaynaklar


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Understanding the importance of statistical engineering
LO02 being able to solve problems in profession and other subjects using statistical methods and techniques
LO03 learning the basic concepts of statistics, the formation and analysis of data
LO04 Developing the ability to identify, interpret and draw appropriate statistical methods for the situation


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 - Having knowledge on “natural and applied sciences” and “basic engineering”; combination of their theoretical and practical knowledge on fisheries engineering applications. 5
PLO02 - 2. Assessment of data scientifically on fisheries engineering, determining and solving the problems 5
PLO03 - 3. Uses theoretical and practical knowledge in the field of fisheries to design; investigates and interprets events and phenomena usig scientific methods and techniques. 3
PLO04 - 4. Collecting data in fisheries science, making the basic experimental studies, evaluating the results, identifying the problems and developing methods of solution 5
PLO05 - 5. Having plan any study related to fisheries science as an individually, managing and consulting. 5
PLO06 - 6.Learning the knowledge by the determining learning needs; developing positive attitude towards lifelong learning 4
PLO07 - 7. Communicating oral and written in expertise field, monitoring the seminars and meeting in expertise field, following the foreign language publication. 3
PLO08 - 8. Improving life-long learning attitude and using the information to the public interest. 0
PLO09 - 9. Creating public awareness about fisheries and having the ability to ensure sustainable use of aquatic resources. 3
PLO10 - 10. Communicating oral and written effectively, participating the seminars and meetings in expertise field, following the foreign language publications. 5
PLO11 - 11. Using the informatics and communicating technology 0
PLO12 - 12. Improves constantly itself , as well as professional development scientific, social, cultural and artistic fields according to his/her interests and abilities identifying needs of learning. 0
PLO13 - 13. Gaining competence to determine the current status of aquatic resources and its sustainable use, water pollution and control, and biotechnology areas. 2
PLO14 - 14. Having ability to promote the study about aquaculture techniques by saving the natural environment, fishery diseases, fishing and processing technology, structure of fishery sector, problems and solution of their expertise field 4
PLO15 - 15. Ability to act in accordance with the regulation, social, scientific, cultural, and ethical values on fisheries field 0


Week Plan

Week Topic Preparation Methods
1 Introduction Reading related sources
2 The basic concepts and symbols Reading related sources
3 Data classification and graph screening Reading related sources
4 Location measurements Reading related sources
5 Dispersion measures Reading related sources
6 Probability and counting rules Reading related sources
7 Chance variables and Probability functions Reading related sources
8 Mid-term exam Preparing for exam
9 Binomial and Poisson distributions Reading related sources
10 Normal distribution Reading related sources
11 Hypothesis testing (Z- and T- Tests) Reading related sources
12 Confidence Interval Reading related sources
13 Chi-square distribution and Chi-square test Reading related sources
14 Regression analyses Reading related sources
15 Correlation analyses Reading related sources
16 FINAL Preparing for exam
17 FINAL Preparing for exam


Assessment (Exam) Methods and Criteria

Assessment Type Midterm / Year Impact End of Term / End of Year Impact
1. Midterm Exam 100 40
General Assessment
Midterm / Year Total 100 40
1. Final Exam - 60
Grand Total - 100


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 2 28
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 8 8
Final Exam 1 16 16
Total Workload (Hour) 108
Total Workload / 25 (h) 4,32
ECTS 4 ECTS

Update Time: 29.04.2025 02:16