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| Course Description |
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| Course Name |
: |
Statistics |
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| Course Code |
: |
SUF201 |
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| Course Type |
: |
Compulsory |
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| Level of Course |
: |
First Cycle |
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| Year of Study |
: |
2 |
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| Course Semester |
: |
Fall (16 Weeks) |
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| ECTS |
: |
4 |
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| Name of Lecturer(s) |
: |
Prof.Dr. MUSTAFA AKAR
Res.Asst. SEDAT GÜNDOĞDU
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| Learning Outcomes of the Course |
: |
Using statistical methods and techniques that are required in solving methods, statistics, systematic thinking, analysis, interpretation, and enhance the ability to draw conclusions for profession and other issues problems
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| Mode of Delivery |
: |
Face-to-Face |
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| Prerequisites and Co-Prerequisites |
: |
None |
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| Recommended Optional Programme Components |
: |
None |
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| Aim(s) of Course |
: |
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. |
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| Course Contents |
: |
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.
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| Language of Instruction |
: |
Turkish |
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| Work Place |
: |
Classrooms of Fisheries Faculty |
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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
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1 |
Introduction |
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Lecture, practise |
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2 |
The basic concepts and symbols |
Reading related sources |
Lecture, practise |
|
3 |
Data classification and graph screening |
Reading related sources |
Lecture, practise |
|
4 |
Location measurements |
Reading related sources |
Lecture, practise |
|
5 |
Dispersion measures |
Reading related sources |
Lecture, practise |
|
6 |
Probability and counting rules |
Reading related sources |
Lecture, practise |
|
7 |
Chance variables and Probability functions |
Reading related sources |
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|
8 |
Mid-term exam |
Preparing for exam |
Lecture, practise |
|
9 |
Binomial and Poisson distributions |
Reading related sources |
Lecture, practise |
|
10 |
Normal distribution |
Reading related sources |
Lecture, practise |
|
11 |
Hypothesis testing (Z- and T- Tests) |
Reading related sources |
Lecture, practise |
|
12 |
Confidence Interval |
Reading related sources |
Lecture, practise |
|
13 |
Chi-square distribution and Chi-square test |
Reading related sources |
Lecture, practise |
|
14 |
Regression analyses |
Reading related sources |
Lecture, practise |
|
15 |
Correlation analyses |
Reading related sources |
Lecture, practise |
|
16/17 |
FINAL |
Preparing for exam |
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Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
 M. AKAR, S. ŞAHİNOĞLU, 1993 İSTATİSTİK. Ç.Ü. ZİRAAT FAK. YAY. ADANA.
H. PÜSKÜLCÜ, F. İKİZ 1983. İSTATİSTİĞE GİRİŞ, E.Ü. MÜHENDİSLİK FAKÜLTESİ DERS KİTABI, İZMİR.
M. AKAR, 1983 APPLİED STATİSTİCS-I FOR ECONOMİCS AND BUSİNESS Ç.Ü. İKTİSADİ VE İDARİ BİLİMLER FAKÜLTESİ FAKÜLTESİ, ADANA.
|
| |
| Required Course Material(s) |
M. AKAR, 1983 APPLİED STATİSTİCS-I FOR ECONOMİCS AND BUSİNESS Ç.Ü. İKTİSADİ VE İDARİ BİLİMLER FAKÜLTESİ FAKÜLTESİ, ADANA.
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Assessment Methods and Assessment Criteria |
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Semester/Year Assessments |
Number |
Contribution Percentage |
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Mid-term Exams (Written, Oral, etc.) |
1 |
60 |
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Homeworks/Projects/Others |
13 |
40 |
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Total |
100 |
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Rate of Semester/Year Assessments to Success |
40 |
| |
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Final Assessments
|
100 |
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Rate of Final Assessments to Success
|
60 |
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Total |
100 |
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| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
|
1 |
Using the informatics and communicating technology |
5 |
|
2 |
Gaining competence to determine the current status of aquatic resources and its sustainable use, water pollution and control, and biotechnology areas. |
2 |
|
3 |
Ability to act in accordance with the regulation, social, scientific, cultural, and ethical values on fisheries field |
1 |
|
4 |
Having knowledge on “natural and applied sciences” and “basic engineering”; combination of their theoretical and practical knowledge on fisheries engineering applications. |
5 |
|
5 |
assessment of data scientifically on fisheries engineering, determining and solving the problems |
5 |
|
6 |
Uses theoretical and practical knowledge in the field of fisheries to design; investigates and interprets events and phenomena usig scientific methods and techniques. |
3 |
|
7 |
Collecting data in fisheries science, making the basic experimental studies, evaluating the results, identifying the problems and developing methods of solution |
5 |
|
8 |
Having plan any study related to fisheries science as an individually, managing and consulting |
5 |
|
9 |
Learning the knowledge by the determining learning needs; developing positive attitude towards lifelong learning |
4 |
|
10 |
Communicating oral and written in expertise field, monitoring the seminars and meeting in expertise field, following the foreign language publication |
3 |
|
11 |
Improving life-long learning attitude and using the information to the public interest. |
4 |
|
12 |
Having skills to apply modern techniques and computational tools necessary for engineering applications. |
3 |
|
13 |
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 |
5 |
|
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 |
|
15 |
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 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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| Student Workload - ECTS |
| Works | Number | Time (Hour) | Total Workload (Hour) |
| Course Related Works |
|
Class Time (Exam weeks are excluded) |
14 |
4 |
56 |
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Out of Class Study (Preliminary Work, Practice) |
14 |
2 |
28 |
| Assesment Related Works |
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Homeworks, Projects, Others |
13 |
1 |
13 |
|
Mid-term Exams (Written, Oral, etc.) |
1 |
2 |
2 |
|
Final Exam |
1 |
2 |
2 |
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Total Workload: | 101 |
| Total Workload / 25 (h): | 4.04 |
| ECTS Credit: | 4 |
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