STAT462 BIOSTATISTICS
Course Code: | 2460462 |
METU Credit (Theoretical-Laboratory hours/week): | 4 (3.00 - 2.00) |
ECTS Credit: | 8.0 |
Department: | Statistics |
Language of Instruction: | English |
Level of Study: | Undergraduate |
Course Coordinator: | Prof.Dr. ÖZLEM İLK DAĞ |
Offered Semester: | Fall and Spring Semesters. |
Course Objectives
This course introduces the students with the special statistical analysis of data collected from biology or medicine.
Course Content
Populations and samples. Types of biological data. Data transformations. Survival data analysis. Life tables. Sample size determination in clinical trials. Measures of association. The odds ratio and some properties. Application of generalized linear models and logistic regression to biological data. Analysis of data from matched samples.
Prerequisite: STAT 156
Course Learning Outcomes
At the end of this course, students are expected to:
- be familiar with the application of some standard statistical procedures, such as logistic regression, hypothesis testing etc., in the field of biology and medicine
- learn about survival analysis for the first time during their undergraduate studies
- carry out some case studies
- hear about some new developments in the field
Program Outcomes Matrix
Level of Contribution | |||||
# | Program Outcomes | 0 | 1 | 2 | 3 |
1 | Applying the knowledge of statistics, mathematics and computer to statistical problems and developing analytical solutions. | ✔ | |||
2 | Defining, modeling and solving real life problems that involve uncertainty, and interpreting results. | ✔ | |||
3 | To decide on the data collection technique, and apply it through experiment, observation, questionnaire or simulation. | ✔ | |||
4 | Analysing small and big volumes of data and interpreting results. | ✔ | |||
5 | Utilizing up-to-date techniques, computer hardware and software required for statistical applications; developing software programs and numerical solutions for specific problems when necessary. | ✔ | |||
6 | Taking part in intradisciplinary and interdisciplinary teamwork, using time efficiently, taking leadership responsibilities and being entrepreneurial. | ✔ | |||
7 | Taking responsibility in individual work and offering authentic solutions. | ✔ | |||
8 | Following contemporary developments and publications in statistical science, conducting research, being open to novelty and thinking critically. | ✔ | |||
9 | Efficiently communicating in Turkish and English to define and analyze statistical problems and to interpret the results. | ✔ | |||
10 | Having a professional and ethical sense of responsibility. | ✔ | |||
11 | Developing computational solutions to statistical problems that cannot be solved analytically. | ✔ | |||
12 | Having theoretical background and developing new theories in statistics, building relations between theoretical and practical knowledge. | ✔ | |||
13 | Serving the society with the expertise in the field. | ✔ |
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution