STAT567 BIOSTATISTICS AND STATISTICAL GENETICS
| Course Code: | 2460567 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Statistics |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Prof.Dr. VİLDA PURUTÇUOĞLU |
| Offered Semester: | Fall or Spring Semesters. |
Course Objectives
This course is designed to provide M.S. students with a strong foundation in biostatistics and statistical genetics, equipping them with the knowledge and skills necessary to analyze complex biological and genetic data. The objectives of the course are to:
Introduce key statistical concepts and methods used in biomedical and genetic research.
Develop proficiency in designing and analyzing studies involving genetic, genomic, and biomedical data.
Explore the statistical models and computational tools commonly used in genome-wide association studies (GWAS), linkage analysis, and high-throughput data analysis.
Foster critical thinking for interpreting results in the context of biological significance and reproducibility.
Prepare students to apply biostatistical and genetic methods in academic, clinical, or industry settings.
Course Content
Introduction to use of statistical methodology in health related sciences. Types of health data. Odds ratio, relative risk. Prospective and retrospective study designs. Cohort, case-control, case-cohort, nested case-control studies. Analysis of survival data. Kaplan-Meier, life tables, Cox`s proportional hazards model. Analysis of case-control data. Unconditional, conditional, polytomous logistic regression. Introduction to genetic epidemiology. Testing Hardy-Weinberg law. Linkeage analysis. Analysis of microarray data. Association studies. Sample size and power. Recent developments in biostatistics and genetic epidemiology.
Course Learning Outcomes
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Apply fundamental biostatistical methods to the analysis of biomedical and public health data.
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Use statistical models to analyze genetic data, including methods for association studies, linkage analysis, and population structure.
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Interpret and communicate results from genetic and genomic data analyses in a scientifically rigorous manner.
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Utilize statistical software tools (e.g., R, PLINK, SAS, or others) to conduct data processing and analysis of complex biological datasets.
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Critically evaluate research articles in biostatistics and statistical genetics, identifying strengths, weaknesses, and appropriate methodologies.
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Design and implement statistical analysis plans for studies involving genetic or genomic data.
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Understand ethical and privacy considerations related to the use of genetic and health-related data in research.
Program Outcomes Matrix
| Level of Contribution | |||||
| # | Program Outcomes | 0 | 1 | 2 | 3 |
| 1 | Ability for converting theoretical, methodological, and computational statistical knowledge into analytical solutions in researches requiring statistical analyses. | ✔ | |||
| 2 | Ability for specifiying problems in real life situations bearing uncertainty, forming hypotheses, modeling, application, and interpreting the results. | ✔ | |||
| 3 | Ability for using current technology, computer softwares for statistical applications, computer programming for specific problems when necessary, writing computer codes for speeding up statistical calculations, organizing and cleaning databases, and preparing them for statistical analyses, and data mining. | ✔ | |||
| 4 | Ability for taking part in intra/inter disciplinary team work, efficient use of time, taking responsibility as a team leader, and entrepreneurship. | ✔ | |||
| 5 | Ability for taking responsibility in solitary work and producing creative solutions. | ✔ | |||
| 6 | Ability for keeping up-to-date with current advancements in statistical sciences, doing research, being open-minded, and adopting critical thinking. | ✔ | |||
| 7 | Ability for effective communication both in Turkish and English in specification of statistical problems, analyes, and interpretation of findings. | ✔ | |||
| 8 | Ability for using the knowledge in the field of expertise for the welfare of the society. | ✔ | |||
| 9 | Ability for suggesting the researchers in a comprehensible way the appropriate statistical methods for problems in fields that use statistics such as economics, finance, industrial engineering, genetics, and medicine and apply if needed. | ✔ | |||
| 10 | Ability for catalyzing discussions and presentations, public speaking, making presentations, communicating topics of expertise to the audiance in a comprehensible way. | ✔ | |||
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution