Rapor Tarihi: 24.02.2026 08:57
| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Statistical Methods Used in Biological Research | BIO618 | Turkish | Compulsory | 4 + 0 | 4.0 | 6.0 |
| Prerequisite Courses | |
| Course Level | Graduate |
| Mode of delivery | Face to face |
| Course Coordinator | Doç. Dr. Salih Tunç KAYA |
| Instructor(s) | Doç. Dr. Salih Tunç KAYA (Güz) |
| Goals | To provide information about control measures used in Biological Sciences |
| Course Content | Comparing tests with sample problems and teaching which tests can be applied to which types of data; Descriptive Statistics, Inferential Statistics and Some Statistical Terms; Descriptive statistics (arithmetic mean, standard deviation, standard error, median, minimum and maximum value) calculations; Introduction of Excel program and its use in descriptive statistics; Introduction of SPSS programs and its use in descriptive statistics; Data types, obtaining, extracting summary data, presenting and interpreting data in Tables and Graphs, introducing tests; Hypotheses, interpretation and statistical decision making, Type I and Type II errors; Chi-square test, its construction and interpretation, regression analysis and interpretation of correlation coefficient; Calculation of dependent and independent sample and t-test, conducting t-test with package programs and interpreting the results; One-way variance analysis and its application with the help of package programs and interpretation of the results; Application of double and multi-way analysis of variance with the help of package programs and interpretation of the results; Kruskal-Wallis Variance Analysis and its application with the help of package programs and interpretation of the results; Mann-Whitney U Test and their application with the help of package programs and interpretation of the results; Comparing tests with sample problems and teaching which tests can be applied to which types of data; Preparing a scientific research project draft, writing a report and applying statistical tests |
| # | Öğrenme Kazanımı |
| 1 | Describes data used in biological research |
| 2 | Explains concepts related to statistics |
| 3 | Explains Sampling and Sampling distributions |
| 4 | Explains hypothesis testing |
| Week | Topics/Applications | Method |
|---|---|---|
| 1. Week | Descriptive Statistics, Inferential Statistics and Some Statistical Terms | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 2. Week | Descriptive statistics (arithmetic mean, standard deviation, standard error, median, minimum and maximum value) calculations | Research, Presentation (Preparation), Practice |
| 3. Week | Comparing tests with sample problems and teaching which tests can be applied to which types of data | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 4. Week | Introducing Graphpad programs and its usage in descriptive statistics | Preparation, After Class Study, Presentation (Preparation), Practice |
| 5. Week | Data types, obtaining, extracting summary data, presenting and interpreting data in Tables and Graphs, introducing tests. | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 6. Week | Hypotheses, interpretation and statistical decision making, Type I and Type II errors | Presentation (Preparation), Practice |
| 7. Week | Chi-square test, its construction and interpretation, regression analysis and interpretation of correlation coefficient | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 8. Week | Calculation of dependent and independent sample and t-test, conducting t-test with package programs and interpreting the results / Mid Term | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 9. Week | One-way variance analysis and its application with the help of package programs and interpretation of the result | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 10. Week | Two- and multi-way analysis of variance and its application with the help of package programs and interpretation of the results | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 11. Week | Kruskal-Wallis Variance Analysis and its application with the help of package programs and interpretation of the results | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 12. Week | Mann-Whitney U Test and its application with the help of package programs and interpretation of the results | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 13. Week | Comparing tests with sample problems and teaching which tests can be applied to which types of data | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| 14. Week | Preparing a scientific research project draft, writing a report and applying statistical tests | Preparation, After Class Study, Research, Presentation (Preparation), Practice |
| No | Program Requirements | Level of Contribution | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Improve the scientific knowledge in the field of Biology to a more advanced level. Use the advenced knowledge to innovate, interpret the results, to apply the results and to design unique projects | ✔ | |||||
| 2 | Gain the ability to identify scientific questions, compare, analyze and solve the problems independently. | ✔ | |||||
| 3 | Gain the skills of using the modern laboratory techniques and analysis methods in the field of biology. | ✔ | |||||
| 4 | Gain the ability to get the information by doing research, to evaluate, interpret and apply it. | ✔ | |||||
| 5 | Gain the ability of discussion, synthesis and applying the scientific knowledge. | ✔ | |||||
| 6 | Gain the ability to design experimental studies, do the applications and analyse the complicated results using advanced skills, like critical thinking, problem solving and deciding. | ✔ | |||||
| 7 | Use the scientific knowledge and apply the ability of problem solving, evaluate and analyse advanced concepts in interdiciplinary fields. | ✔ | |||||
| 8 | Gain the scientific knowledge to set up communication with the collegues. Gain the ability to follow and use of the literature. Gain the ability to share or present the results of his/her own studies with the scientists during a scientific conference, workshop or seminar. | ✔ | |||||
| 9 | Participate scientific collaborations effectively and lead a scientific study if necessary. | ✔ | |||||
| 10 | Follow the innovations in the field of biology. Gain the ability to find resources and to use the databases. | ✔ | |||||
| 11 | Find new or strategical approaches to solve an unpredicted or advanced problems. | ✔ | |||||
| 12 | Improve scientific knowledge where there is a little or limited data present. Gain the ability to connect the information from different scientific diciplines. | ✔ | |||||
| 13 | Find unique ideas and get in contact with the professionals in scientific topics using his/her knowledge and skills. | ✔ | |||||
| 14 | Have the ability to read, understand, speak and write a foreign language in order to contact with the scientists from all over the World. | ✔ | |||||
| 15 | Follow novel developments in computational software and hardware systems related with biology, use this knowledge and skill in research. | ✔ | |||||
| 16 | Obey the ethical regulations and watch the ethical issues while designing a scientific study, collecting data, evaluating and publishing them. | ✔ | |||||
| 17 | Adopt life-long learning strategies during performing scientific studies. | ✔ | |||||
| Program Requirements | DK1 | DK2 | DK3 | DK4 |
|---|---|---|---|---|
| PY1 | 5 | 5 | 5 | 5 |
| PY2 | 5 | 5 | 5 | 5 |
| PY3 | 4 | 4 | 4 | 4 |
| PY4 | 5 | 5 | 5 | 5 |
| PY5 | 5 | 5 | 5 | 5 |
| PY6 | 4 | 4 | 4 | 4 |
| PY7 | 4 | 4 | 4 | 4 |
| PY8 | 4 | 4 | 4 | 4 |
| PY9 | 3 | 3 | 3 | 3 |
| PY10 | 5 | 5 | 5 | 5 |
| PY11 | 5 | 5 | 5 | 5 |
| PY12 | 5 | 5 | 5 | 5 |
| PY13 | 3 | 3 | 3 | 3 |
| PY14 | 3 | 3 | 3 | 3 |
| PY15 | 5 | 5 | 5 | 5 |
| PY16 | 5 | 5 | 5 | 5 |
| PY17 | 5 | 5 | 5 | 5 |
| 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 | 4 | 56 |
|
Ders Dışı |
Preparation, After Class Study | 14 | 1 | 14 |
| Presentation (Preparation) | 14 | 2 | 28 | |
| Practice | 14 | 1 | 14 | |
| Other Activities | 14 | 2.5 | 35 | |
|
Sınavlar |
Midterm 1 | 1 | 2 | 2 |
| Homework 1 | 1 | 2 | 2 | |
| Final | 1 | 2 | 2 | |
| Total Workload | 153 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 6.0 | ||
