| Course Title | Code | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|
| Biostatistics | BIS501 | 2 + 2 | 3.0 | 8.0 |
| Prerequisites | None |
| Language of Instruction | Turkish |
| Course Level | Graduate |
| Course Type | |
| Mode of delivery | Face-to-Face |
| Course Coordinator |
Prof. Dr. Şengül CANGÜR |
| Instructor(s) | |
| Assistants | |
| 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. |
| Learning Outcomes |
- 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. - 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. - Learn basic biostatistic concepts, classify variables according to types and usage, define the types of variables in the package program. - Learn the central tendency measures, calculate them manually and through package programs, know the differences between them and choose where to use. - 5. Learn the variation measures, calculate them manually and through package programs, know the differences between them and choose where to use. - 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. - 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. - Differentiate between parametric and nonparametric hypotheses and explain the preferred cases, know parametric and nonparametric hypothesis tests used for basic purposes. - Learn the tests used to compare the mean, median and proportion of two independent samples, apply them through package program and interpret the results. - 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. - Learn the tests used to compare the mean, median and proportion of two dependent samples, apply them through package program and interpret the results. - 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. - Learn simple and partial correlation analysis, apply it through package program and interpret its results, perform simple linear regression analysis and interpret its results. - 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. - 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 | Learning Methods |
|---|---|---|
| 1. Week | Introduction to Biostatistics | Course Hours |
| 2. Week | Basic Biostatistics Concepts | Course Hours Preparation, After Class Study |
| 3. Week | Classification of Data | Other Activities Preparation, After Class Study Research Course Hours |
| 4. Week | Descriptive Statistics | Course Hours Preparation, After Class Study Other Activities |
| 5. Week | Tables and Graphs | Other Activities Preparation, After Class Study Course Hours |
| 6. Week | Concept of Hypothesis, Parametric and Nonparametric Hypothesis Tests | Course Hours Preparation, After Class Study Other Activities |
| 7. Week | Two and More Sample Tests in Independent Groups | Preparation, After Class Study Research Other Activities Course Hours |
| 8. Week | Two and More Sample Tests in Dependent Groups | Research Other Activities Course Hours Preparation, After Class Study |
| 9. Week | Simple, Partial Linear Correlation and Linear Regression Analysis | Other Activities Research Course Hours Preparation, After Class Study |
| 10. Week | Methods used to Determine Sample and Sample Size | Course Hours Preparation, After Class Study Research Other Activities |
| 11. Week | Sample Size Calculation for Some Hypothesis Tests | Other Activities Preparation, After Class Study Research Course Hours |
| 12. Week | Selection of Appropriate Sampling Method | Other Activities Course Hours Preparation, After Class Study |
| 13. Week | Research Types and Basic Characteristics of Researches | Other Activities Course Hours Preparation, After Class Study Research |
| 14. Week | Common Mistakes in Researches | Research Other Activities Course Hours Preparation, After Class Study |
| Ankaralı H, Cangür S, Sungur MA Formülsüz Biyoistatistik, İstanbul: Betim Basım, ISBN: 6058695733, 2015. |
| Sümbüloglu K ve Sümbüloğlu V. Biyoistatistik. Ankara: Seçkin Yayıncılık, 2010.. |
| Özdamar K. Pasw ile Biyoistatistik. Eskişehir: Kaan Kitabevi, 2013. |
| Alpar R. Spor, Sağlık ve Eğitim Bilimlerinden Örneklerle UYGULAMALI İSTATİSTİK ve GEÇERLİK-GÜVENİRLİK. Ankara: Detay Yayıncılık, 2014. |
| Daniel, Wayne W. Biostatistics 9th Edition, New York: John Wiley & Sons, 2013. |
| Program Requirements | Contribution Level | DK1 | DK2 | DK3 | DK4 | DK5 | DK6 | DK7 | DK8 | DK9 | DK10 | DK11 | DK12 | DK13 | DK14 | DK15 | Measurement Method |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PY1 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 40,60 |
| PY2 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 40,60 |
| PY3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 40,60 |
| PY4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 40,60 |
| PY5 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 40,60 |
| PY6 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 40,60 |
| PY7 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 40,60 |
| PY8 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 40,60 |
| PY9 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 40,60 |
| PY10 | 2 | 0 | 0 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 40,60 |
| PY11 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 40,60 |
| PY12 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | 40,60 |
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| Course's Level of contribution | None | Very Low | Low | Fair | High | Very High |
| Method of assessment/evaluation | Written exam | Oral Exams | Assignment/Project | Laboratory work | Presentation/Seminar |
| Event | Quantity | Duration (Hour) | Total Workload (Hour) |
|---|---|---|---|
| Course Hours | 14 | 4 | 56 |
| Preparation, After Class Study | 13 | 2 | 26 |
| Research | 8 | 2 | 16 |
| Other Activities | 12 | 0.5 | 6 |
| Homework 1 | 14 | 1 | 14 |
| Final | 1 | 2 | 2 |
| Practice | 14 | 2 | 28 |
| Classroom Activities | 14 | 4 | 56 |
| Total Workload | 204 | ||
| ECTS Credit of the Course | 8.0 | ||
