ARCHITECTURE | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
BME3005 | Biostatistics | Spring | 2 | 2 | 3 | 6 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Non-Departmental Elective |
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 |
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. |
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. |
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 |
Course Notes / Textbooks: | Primer of Biostatistics, Stanton A. Glantz, McGraw-Hill, 7th Edition Fundamental of Biostatistics, Bernard Rosner, Cengage Learning, 8th Edition |
References: |
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 |
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 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Using the theoretical/conceptual and practical knowledge acquired for architectural design, design activities and research. | |
2) | Identifying, defining and effectively discussing aesthetic, functional and structural requirements for solving design problems using critical thinking methods. | |
3) | Being aware of the diversity of social patterns and user needs, values and behavioral norms, which are important inputs in the formation of the built environment, at local, regional, national and international scales. | |
4) | Gaining knowledge and skills about architectural design methods that are focused on people and society, sensitive to natural and built environment in the field of architecture. | |
5) | Gaining skills to understand the relationship between architecture and other disciplines, to be able to cooperate, to develop comprehensive projects; to take responsibility in independent studies and group work. | |
6) | Giving importance to the protection of natural and cultural values in the design of the built environment by being aware of the responsibilities in terms of human rights and social interests. | |
7) | Giving importance to sustainability in the solution of design problems and the use of natural and artificial resources by considering the social, cultural and environmental issues of architecture. | |
8) | Being able to convey and communicate all kinds of conceptual and practical thoughts related to the field of architecture by using written, verbal and visual media and information technologies. | |
9) | Gaining the ability to understand and use technical information about building technology such as structural systems, building materials, building service systems, construction systems, life safety. | |
10) | Being aware of legal and ethical responsibilities in design and application processes. |