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 Outcomes0123
1Applying the knowledge of statistics, mathematics and computer to statistical problems and developing analytical solutions.
2Defining, modeling and solving real life problems that involve uncertainty, and interpreting results.
3To decide on the data collection technique, and apply it through experiment, observation, questionnaire or simulation.
4Analysing small and big volumes of data and interpreting results.
5Utilizing up-to-date techniques, computer hardware and software required for statistical applications; developing software programs and numerical solutions for specific problems when necessary.
6Taking part in intradisciplinary and interdisciplinary teamwork, using time efficiently, taking leadership responsibilities and being entrepreneurial.
7Taking responsibility in individual work and offering authentic solutions.
8Following contemporary developments and publications in statistical science, conducting research, being open to novelty and thinking critically.
9Efficiently communicating in Turkish and English to define and analyze statistical problems and to interpret the results.
10Having a professional and ethical sense of responsibility.
11Developing computational solutions to statistical problems that cannot be solved analytically.
12Having theoretical background and developing new theories in statistics, building relations between theoretical and practical knowledge.
13Serving the society with the expertise in the field.

0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution