| Course Title | Code | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|
| Biostatistics | HEM501 | 2 + 0 | 2.0 | 4.0 |
| Prerequisites | None |
| Language of Instruction | Turkish |
| Course Level | Graduate |
| Course Type | |
| Mode of delivery | An interactive lesson, Project, Seminar |
| Course Coordinator |
Assoc. Prof. Dr. Mehmet Ali SUNGUR |
| Instructors |
Mehmet Ali SUNGUR |
| Assistants | |
| Goals | To teach basic statistical concepts and methods to students by examples and applications in health sciences, to provide understanding and evaluating the statistical analysis used in the literature of their own study fields. |
| Course Content | This course includes that; Basic statistical concepts such as: statistics and biostatistics, population, sample, statistic, parameter, data, variable, types of data, and etc., Descriptive statistics: grouping the data, measures of central tendency, measures of location, histogram, bar graph, stem & leaf graph, box-plot, etc, Descriptive statistics: measures of dispersion, error bar graph, etc, Examining the association among the variables by tables and graphics: Cross tables, tables regarding descriptive statistics (mean, s. deviation, etc.), multivariate applications of basic graphics, scatter plots, etc., Standardization (z and T scores). Theoretical distributions: Normal distribution, and normality transformations. Tests and graphs for normality. Sampling distributions and confidence intervals, Research methods. Introduction to hypothesis tests: Aims and stages of hypothesis tests, possible types of errors, p and alpha values, power, effect size, decision process, Hypothesis tests: Parametric and nonparametric one sample tests. Parametric and nonparametric independent two sample tests, Hypothesis tests: Parametric and nonparametric two independent sample tests, Hypothesis tests: Parametric and nonparametric dependent two-sample tests). Parametric and nonparametric two dependent sample tests, Measures of association: Pearson correlatin coefficient, Spearman correlation coefficient, Phi, Cramer V, Eta, etc., Simple and multiple linear regression analysis, Simple and multiple linear regression analysis and examining an article. |
| Learning Outcomes |
- Decide to proper basic statistical analysis - Do calculations and analysis individually - Interpret the findings - Understand statistical analysis used in the literature of their own study fields - Criticize statistical analysis used in the literature of their own study fields - Have sufficient theoretical and practical basis required in advanced statistical courses - Can plan and implement a scientific research in the field of Surgical Nursing, can analyzes and reports the obtained data. |
| Week | Topics | Learning Methods |
|---|---|---|
| 1. Week | Basic statistical concepts such as: statistics and biostatistics, population, sample, statistic, parameter, data, variable, types of data, and etc. | |
| 2. Week | Descriptive statistics: grouping the data, measures of central tendency, measures of location, histogram, bar graph, stem & leaf graph, box-plot, etc. | |
| 3. Week | Descriptive statistics: measures of dispersion, error bar graph, etc. | |
| 4. Week | Examining the association among the variables by tables and graphics: Cross tables, tables regarding descriptive statistics (mean, s. deviation, etc.), multivariate applications of basic graphics, scatter plots, etc. | |
| 5. Week | Standardization (z and T scores). Theoretical distributions: Normal distribution, and normality transformations. Tests and graphs for normality. Sampling distributions and confidence intervals | |
| 6. Week | 1st Midterm Examination | |
| 7. Week | Research methods. Introduction to hypothesis tests: Aims and stages of hypothesis tests, possible types of errors, p and alpha values, power, effect size, decision process | |
| 8. Week | Hypothesis tests: Parametric and nonparametric one sample tests. Parametric and nonparametric independent two sample tests. | |
| 9. Week | Hypothesis tests: Parametric and nonparametric two independent sample tests. | |
| 10. Week | Hypothesis tests: Parametric and nonparametric dependent two-sample tests). Parametric and nonparametric two dependent sample tests . | |
| 11. Week | 2nd Midterm Examination | |
| 12. Week | Measures of association: Pearson correlatin coefficient, Spearman correlation coefficient, Phi, Cramer V, Eta, etc. | |
| 13. Week | Simple and multiple linear regression analysis. | |
| 14. Week | Simple and multiple linear regression analysis and examining an article. |
| 1. Sümbüloglu K ve Sümbüloğlu V. Biyoistatistik. Seçkin Yayıncılık, Ankara, 2010. 2. Özdamar K. Pasw ile Biyoistatistik. Kaan Kitabevi, Eskişehir, 2013. 3. Alpar R. Spor, Sağlık ve Eğitim Bilimlerinden Örneklerle Uygulamalı İstatistik ve Geçerlik-Güvenirlik. Detay Yayıncılık, Ankara, 2018. 4. Daniel, Wayne W. Biostatistics 9th Edition, New York: John Wiley&Sons, 2013. |
| Program Requirements | Contribution Level | DK1 | DK2 | DK3 | DK4 | DK5 | DK6 | DK7 | Measurement Method |
|---|
| 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) |
|---|---|---|---|
| Midterm 1 | 1 | 2 | 2 |
| Midterm 2 | 1 | 2 | 2 |
| Homework 1 | 14 | 1 | 14 |
| Final | 1 | 2 | 2 |
| Total Workload | 20 | ||
| ECTS Credit of the Course | 4.0 | ||
