| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Statistics | TB102 | Turkish | Compulsory | 2. Semester | 3 + 0 | 3.0 | 4.0 |
| Prerequisite Courses | |
| Course Level | Undergraduate |
| Mode of delivery | Face to face |
| Course Coordinator | |
| Instructor(s) | |
| Goals | Student enables information about the basic statistical concepts and methods and they learn implementation and interpretation of these basic statistical methods. |
| Course Content | Indroduction to statistical analyses, general terms, presentation of data and summarization, identifcate statistics, probability and their distrubitions (binomial, poissonial and normal), statistical comments, hipothesis, analyses of the regression and correlations, analyses of the data. |
| # | Öğrenme Kazanımı |
| 1 | Students learn the basic concepts of statistics |
| 2 | Establish statistical estimation and hypothesis |
| 3 | Understand to application of basic statistical methods |
| 4 | Learn to evaluation of statistical outputs |
| Week | Topics/Applications | Method |
|---|---|---|
| 1. Week | Basic terms and definitions | Interview Presentation (Preparation) Class Hours |
| 2. Week | Variable types, frequency distributions, descriptive statistics for example, mode, median, | Presentation (Preparation) Class Hours Interview |
| 3. Week | Change measures, the change range, standard deviation, variance | Interview Class Hours Presentation (Preparation) |
| 4. Week | The theory of probability and chance variables, event, probability, determining the number of events | Presentation (Preparation) Class Hours Interview |
| 5. Week | Discrete chance variables, continuous chance variables | Interview Presentation (Preparation) Class Hours |
| 6. Week | Probability distributions for discrete variables, binomial distributions, Poisson distributions | Presentation (Preparation) Interview Class Hours |
| 7. Week | Uniform distribution, gamma type of probability distributions, Weibull probability distribution, implementation of normal distribution to Binomial distribution | Interview Class Hours Presentation (Preparation) |
| 8. Week | Midterm exam | |
| 9. Week | Statistical interpretation, statistical estimator types, point and interval estimation for the average population | Presentation (Preparation) Class Hours Interview |
| 10. Week | Hypothesis testing, large and small sample tests, t distribution, the comparison of two means | Interview Class Hours Presentation (Preparation) |
| 11. Week | The chi-square distribution, confidence intervals for variance and controls for hypothesis testing, comparison of two variance and F test | Presentation (Preparation) Interview Class Hours |
| 12. Week | The relationship between variables, linear relations, examination of the regression equation | Interview Class Hours Presentation (Preparation) |
| 13. Week | Correlation, the correlation coefficient calculation, control and homogeneity testing | Class Hours Presentation (Preparation) |
| 14. Week | Trial design and analysis, randomized plots and blocks, Latin square design experiment, comparing the averages and nonparametric tests and applications | Interview Class Hours Presentation (Preparation) |
| No | Program Requirements | Level of Contribution | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Skill of apply basic science and engineering knowledge and principles to Agricultural Engineering problems | ✔ | |||||
| 2 | He/she can use the information in his/her area to solve problems and use his/her applying skills in interdiscipliner studies | ✔ | |||||
| 3 | He/she can conduct an independed research in a specified area related with field crops | ✔ | |||||
| 4 | He/she can develop new strategic approaches and can produce solutions taking the responsibility, to the problems unexpected or faced in the practice related with field crops | ✔ | |||||
| 5 | He/she can develope a positive attitute to the lifelong education by knowledge and skils gained in field crops area | ✔ | |||||
| 6 | He/she can control the data collection, evaluation and publication, keeping cultural and scientific and ethical values and can teach these values. | ✔ | |||||
| 7 | He/she can develop strategy, policy and applying plans and can discuss the results obtained in the framework of quality management periods | ✔ | |||||
| 8 | Self-development skill following the developments in science and technology | ✔ | |||||
| 9 | He/she can transfer his/her works and the developlmets in his/her area in a written, audial and visual way. | ✔ | |||||
| 10 | He/she can evaluate the knowledge and skills in field crops area in specified level with a criticising approach | ✔ | |||||
| Program Requirements | DK1 | DK2 | DK3 | DK4 |
|---|---|---|---|---|
| PY1 | 3 | 3 | 3 | 3 |
| PY2 | 3 | 3 | 3 | 3 |
| PY3 | 3 | 3 | 3 | 3 |
| PY4 | 2 | 2 | 2 | 2 |
| PY5 | 3 | 3 | 3 | 3 |
| PY6 | 3 | 3 | 3 | 3 |
| PY7 | 2 | 2 | 2 | 2 |
| PY8 | 4 | 4 | 4 | 4 |
| PY9 | 2 | 2 | 2 | 2 |
| PY10 | 2 | 2 | 2 | 2 |
| Ders Kitabı veya Notu | Ders Kitabı veya Ders Notu bulunmamaktadır. |
|---|---|
| Diğer Kaynaklar |
|
| ECTS credits and course workload | Quantity | Duration (Hour) | Total Workload (Hour) | |
|---|---|---|---|---|
|
Ders İçi |
Class Hours | 14 | 3 | 42 |
|
Ders Dışı |
Preparation, After Class Study | 10 | 1 | 10 |
|
Sınavlar |
Midterm 1 | 1 | 20 | 20 |
| Final | 1 | 30 | 30 | |
| Total Workload | 102 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 4.0 | ||
