BAHÇEŞEHİR UNIVERSITY BİLGİ PAKETİ / DERS KATALOĞU
| MOLECULAR BIOLOGY AND GENETICS | |||||
| Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 | ||
Course Introduction and Application Information
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| BME3005 | Biostatistics | Spring | 2 | 2 | 3 | 6 |
Basic information
| Language of instruction: | English |
| Type of course: | Must Course |
| Course Level: | Bachelor’s Degree (First Cycle) |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Dr. Öğr. Üyesi BURCU TUNÇ ÇAMLIBEL |
| Course Lecturer(s): |
Dr. Öğr. Üyesi BURCU TUNÇ ÇAMLIBEL |
| Recommended Optional Program Components: | None |
| Course Objectives: | - The course provides an introduction to selected important topics in biostatistical concepts and reasoning. This course represents an introduction to the field and provides a survey of data and data types. Specific topics include tools for describing central tendency and variability in data; methods for performing inference on population means and proportions via sample data; statistical hypothesis testing and its application to group comparisons; issues of power and sample size in study designs; and random sample and other study types; regression analysis, confidence intervals, correlations |
Learning Outcomes
|
The students who have succeeded in this course; - The students who have succeeded in this course; I. Interpret statistical results correctly, effectively, and in context. II. Select an appropriate test for comparing two or more populations, and interpret and explain a p-value III. Understand the concept of the power of data. IV. Calculate and interpret confidence intervals for population means and proportions V. Understand regression analysis and correlation of variables. |
Course Content
| Design of Experiments, Statistical programming: , Exploratory Data Analysis and Descriptive Statistics, Probability Theory, Sampling Distributions and the Central Limit Theorem, Estimation, Statistical Inference, Contingency tables, Nonparametric Tests, Power and sample size, ANOVA, Correlation and Regression, Logistic regression, Survival Analysis, applications on biological datasets. |
Weekly Detailed Course Contents
| Week | Subject | Related Preparation |
| 1) | Introduction to biostatistics | |
| 2) | Descriptive Statistics | |
| 3) | Probability Theory | |
| 4) | Sampling Distributions and the Central Limit Theorem | |
| 5) | ANOVA | |
| 6) | The Special Case of Two Groups: the t test | |
| 7) | Contingency tables, Chi Square Test, z-test | |
| 8) | Fisher Exact Test, Relative Risk, Odds Ratio | |
| 9) | Power and Sample size | |
| 10) | Paired t-test, Repeated Measures of Analysis of Variance, McNemar's Test | |
| 11) | Nonparametric Tests: Mann-Whitney Rank-Sum Test, Wilcoxon Signed-Rank Test | |
| 12) | Nonparametric Tests: Kruskal-Wallis Test, Friedman Test | |
| 13) | Confidence Intervals | |
| 14) | Correlation and Regression |
Sources
| Course Notes / Textbooks: | Primer of Biostatistics, Stanton A. Glantz, McGraw-Hill, 7th Edition Fundamental of Biostatistics, Bernard Rosner, Cengage Learning, 8th Edition |
| References: |
Evaluation System
| Semester Requirements | Number of Activities | Level of Contribution |
| Quizzes | 5 | % 30 |
| Midterms | 1 | % 30 |
| Final | 1 | % 40 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| Total | % 100 | |
ECTS / Workload Table
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 3 | 42 |
| Study Hours Out of Class | 14 | 7 | 98 |
| Quizzes | 5 | 1 | 5 |
| Midterms | 1 | 3 | 3 |
| Final | 1 | 3 | 3 |
| Total Workload | 151 | ||
Contribution of Learning Outcomes to Programme Outcomes
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Utilize the wealth of information stored in computer databases to answer basic biological questions and solve problems such as diagnosis and treatment of diseases. | 3 |
| 2) | Acquire an ability to compile and analyze biological information, clearly present and discuss the conclusions, the inferred knowledge and the arguments behind them both in oral and written format. | 5 |
| 3) | Develop critical, creative and analytical thinking skills. | 5 |
| 4) | Develop effective communication skills and have competence in scientific speaking, reading and writing abilities in English and Turkish. | 4 |
| 5) | Gain knowledge of different techniques and methods used in genetics and acquire the relevant laboratory skills. | 3 |
| 6) | Detect biological problems, learn to make hypothesis and solve the hypothesis by using variety of experimental and observational methods. | 5 |
| 7) | Gain knowledge of methods for collecting quantitative and qualitative data and obtain the related skills. | 2 |
| 8) | Conduct research through paying attention to ethics, human values and rights. Pay special attention to confidentiality of information while working with human subjects. | 5 |
| 9) | Obtain basic concepts used in theory and practices of molecular biology and genetics and establish associations between them. | 4 |
| 10) | Search and use literature to improve himself/herself and follow recent developments in science and technology. | 4 |
| 11) | Be aware of the national and international problems in the field and search for solutions. | 4 |