Rapor Tarihi: 13.04.2026 11:20
| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Biostatistics | BIS501 | Turkish | Compulsory | 2 + 2 | 3.0 | 8.0 |
| Prerequisite Courses | |
| Course Level | Graduate |
| Mode of delivery | Face-to-Face |
| Course Coordinator | Prof. Dr. Şengül CANGÜR |
| Instructor(s) | |
| Goals | Providing students to understand basic statistical concepts and methods with examples and applications. Providing students to capable of solving and interpreting basic statistical problems on his own. |
| Course Content | The main reasons for giving this course are; Introducing the concepts and methods of biostatistics to the students from outside the field, and the students who come from the field teach the basic applications of biostatistics most frequently used in the field of health. When this aim is taken into consideration, the definition and usage of the content of the course, basic statistical concepts, classification of variables, descriptive statistics, tables and graph types, variable distributions and properties, sampling distributions of statistics, concept of hypothesis and error types, Single sample hypothesis tests, simple correlation and regression analysis, general information about parametric and nonparametric statistics, health statistics, sensitivity and selectivity calculation, sample size detection and sampling methods. In addition, the place of implementation of the topics covered in this course and the implementation steps will be discussed. |
| # | Öğrenme Kazanımı |
| 1 | Learn the definition of statistical and biostatistics sciences, learn how and where to use the methods and principles of biostatistics science, decide on the conditions and situations required for biostatistics consultancy. |
| 2 | Describe the definition of the data, learn the characteristics of the data must have and the basic concepts of data collection, and can make data entry, data manipulation. |
| 3 | Learn basic biostatistic concepts, classify variables according to types and usage, define the types of variables in the package program. |
| 4 | Learn the central tendency measures, calculate them manually and through package programs, know the differences between them and choose where to use. |
| 5 | 5. Learn the variation measures, calculate them manually and through package programs, know the differences between them and choose where to use. |
| 6 | Define the tables and graphs, learn the basic rules for drawing tables and graphs, draw appropriate tables and graphs, and decide which graph to use in which case. |
| 7 | Define the concept of hypothesis, learn the meaning of the hypothesis test, define the errors that will occur after the hypothesis test, learn the power of test and classify hypothesis tests. |
| 8 | Differentiate between parametric and nonparametric hypotheses and explain the preferred cases, know parametric and nonparametric hypothesis tests used for basic purposes. |
| 9 | Learn the tests used to compare the mean, median and proportion of two independent samples, apply them through package program and interpret the results. |
| 10 | Learn the tests used to compare the mean, median, and proportion of more than two independent samples, apply them through package program and interpret the results. |
| 11 | Learn the tests used to compare the mean, median and proportion of two dependent samples, apply them through package program and interpret the results. |
| 12 | Learn the tests used to compare the mean, median, and proportion of more than two dependent samples, apply them through package program and interpret the results. |
| 13 | Learn simple and partial correlation analysis, apply it through package program and interpret its results, perform simple linear regression analysis and interpret its results. |
| 14 | Know the issues to be considered in determining sample size, calculate the appropriate sample size for the main problems, and decide how to select the samples with the most commonly used sampling methods. |
| 15 | Know the types of scientific research, basic features of these types and differences between them, and know the common mistakes about statistical concepts, methods and principles at various stages of researches. |
| Week | Topics/Applications | Method |
|---|---|---|
| 1. Week | Introduction to Biostatistics | |
| 2. Week | Basic Biostatistics Concepts | Preparation, After Class Study |
| 3. Week | Classification of Data | Preparation, After Class Study, Research, Other Activities |
| 4. Week | Descriptive Statistics | Preparation, After Class Study, Other Activities |
| 5. Week | Tables and Graphs | Preparation, After Class Study, Other Activities |
| 6. Week | Concept of Hypothesis, Parametric and Nonparametric Hypothesis Tests | Preparation, After Class Study, Other Activities |
| 7. Week | Two and More Sample Tests in Independent Groups | Preparation, After Class Study, Research, Other Activities |
| 8. Week | Two and More Sample Tests in Dependent Groups | Preparation, After Class Study, Research, Other Activities |
| 9. Week | Simple, Partial Linear Correlation and Linear Regression Analysis | Preparation, After Class Study, Research, Other Activities |
| 10. Week | Methods used to Determine Sample and Sample Size | Preparation, After Class Study, Research, Other Activities |
| 11. Week | Sample Size Calculation for Some Hypothesis Tests | Preparation, After Class Study, Research, Other Activities |
| 12. Week | Selection of Appropriate Sampling Method | Preparation, After Class Study, Other Activities |
| 13. Week | Research Types and Basic Characteristics of Researches | Preparation, After Class Study, Research, Other Activities |
| 14. Week | Common Mistakes in Researches | Preparation, After Class Study, Research, Other Activities |
| No | Program Requirements | Level of Contribution | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | The biostatistics specialist will have the knowledge to help the faculty member in conducting the biostatistics course and to practice the laboratory in the faculties. | ✔ | |||||
| 2 | At high schools, the biostatistics specialist will have the knowledge, experience and experience to give the basic biostatistics course on their own | ✔ | |||||
| 3 | The biostatistics specialist will be able to ask questions, to make contributions and to criticize questions about scientific presentations at seminars, congresses or symposium. | ✔ | |||||
| 4 | Information about the field of the biostatistics specialist will be used exchange information with the thesis supervisor, transfer to the others in discussion of article and seminar presentation etc. events. | ✔ | |||||
| 5 | The biostatistics specialist will be able to consult biostatistics to thesis researches and basic scientific researches and will be able to analyze data using various statistical programs and interpret the results. | ✔ | |||||
| 6 | The biostatistics specialist will have knowledge of biostatistics that can make planning and execution of researches. | ✔ | |||||
| 7 | The biostatistics specialist will be able to make the planning, execution and reporting stages of scientific research related to his/her field alone. | ✔ | |||||
| 8 | The biostatistics specialist will be able to have knowledge of the theoretical biostatistics that can contribute to the biostatistics science and apply basic biostatistics methods. | ✔ | |||||
| 9 | The biostatistics specialist will have enough mathematical statistics knowledge to be able to decide appropriate statistical analysis and to be able to analyze the results correctly. | ✔ | |||||
| 10 | The biostatistics specialist will be able to make comments about the concept, methods and principles of biostatistics mentioned in the scientific researches obtained as a result of the literature review and will be able to give an idea about the usage in the literature. | ✔ | |||||
| 11 | The biostatistics specialist will be able to collect data to reduce health problems and improve health status of the region in which they work, to assess risk, and to identify risk factors for diseases that can make cause-outcome relationship and cause common or most death and disability, which may be comparable to previous periods and different regions. | ✔ | |||||
| 12 | The biostatistics specialist will be able to calculate, interpret and graph the necessary health statistics to protect community health and to take various measures in health services. | ✔ | |||||
| Program Requirements | DK1 | DK2 | DK3 | DK4 | DK5 | DK6 | DK7 | DK8 | DK9 | DK10 | DK11 | DK12 | DK13 | DK14 | DK15 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PY1 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |
| PY2 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |
| PY3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| PY4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| PY5 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| PY6 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
| PY7 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| PY8 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| PY9 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| PY10 | 0 | 0 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
| PY11 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
| PY12 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| 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 | 13 | 2 | 26 |
| Research | 8 | 2 | 16 | |
| Other Activities | 12 | 0.5 | 6 | |
|
Sınavlar |
Homework | 14 | 1 | 14 |
| Final | 1 | 2 | 2 | |
| Practice | 14 | 2 | 28 | |
| Classroom Activities | 14 | 4 | 56 | |
| Total Workload | 204 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 8.0 | ||
