Faculty: INSTITUTE OF GRADUATE PGROGRAMS The Biostatistics major focuses on the application of statistical methods to biological, medical, and health-related fields. Students gain skills in statistical theory, data analysis, experimental design, epidemiology, and bioinformatics, preparing for careers in research, public health, pharmaceuticals, healthcare, and related fields. **Learning Objectives:** - Understand the principles of biostatistics and their application to biological and health sciences. - Develop skills in statistical theory and data analysis. - Learn experimental design and sampling techniques. - Explore epidemiological methods and study designs. - Analyze bioinformatics and computational biology tools. - Develop critical thinking, problem-solving, and analytical skills. - Gain practical experience through research projects and internships. **Major Outline:** 1. **Introduction to Biostatistics** - Overview of biostatistics principles, history, and current trends. 2. **Statistical Theory** - Fundamentals of probability theory and statistical inference. 3. **Data Analysis** - Techniques for analyzing and interpreting biological and health data. 4. **Experimental Design** - Principles of designing and conducting experiments in biological and health sciences. 5. **Epidemiology** - Methods for studying the distribution and determinants of health and disease. 6. **Bioinformatics** - Use of computational tools and algorithms to analyze biological data. 7. **Survival Analysis** - Techniques for analyzing time-to-event data in medical and health research. 8. **Clinical Trials** - Principles of designing, conducting, and analyzing clinical trials. 9. **Statistical Software** - Use of statistical software for data analysis and visualization. 10. **Genomics and Proteomics** - Statistical methods for analyzing genomic and proteomic data. 11. **Research Methods in Biostatistics** - Methods for conducting and evaluating biostatistical research. 12. **Internship/Practicum** - Real-world experiences in research institutions, pharmaceutical companies, public health agencies, or related organizations. 13. **Capstone Project** - Comprehensive project applying biostatistics skills, such as conducting a data analysis study, designing an experimental protocol, or developing a bioinformatics tool. **Assessment Methods:** - Biostatistics principles analyses - Statistical theory projects - Data analysis projects - Experimental design projects - Epidemiology projects - Bioinformatics projects - Survival analysis projects - Clinical trials projects - Statistical software projects - Genomics and proteomics projects - Research methods projects - Internship/practicum reports - Capstone projects and presentations **Recommended Textbooks:** - "Introduction to Biostatistics" - "Statistical Theory" - "Data Analysis" - "Experimental Design" - "Epidemiology" - "Bioinformatics" - "Survival Analysis" - "Clinical Trials" - "Statistical Software" - "Genomics and Proteomics" - "Research Methods in Biostatistics" **Prerequisites:** Basic knowledge of mathematics, statistics, and an interest in biostatistics and health sciences. **Major Duration:** Typically 4 years for a bachelor's degree in Biostatistics. **Certification:** Graduates may pursue certifications such as: - Certified Biostatistician (CB) - Certified Health Data Analyst (CHDA) - Certifications in specific biostatistical software and technologies **Target Audience:** Aspiring biostatisticians, data analysts, epidemiologists, bioinformaticians, clinical trial managers, and professionals seeking careers in research institutions, pharmaceutical companies, public health agencies, healthcare organizations, and related fields. This major equips students with the statistical, analytical, and computational skills needed to excel in biostatistics, supporting careers in various roles within research institutions, pharmaceutical companies, public health agencies, healthcare organizations, and related fields. The program provides a comprehensive education in biostatistics principles, statistical theory, data analysis, experimental design, epidemiology, bioinformatics, survival analysis, clinical trials, statistical software, genomics, proteomics, research methods, and practical experience through research projects and internships, preparing students for successful careers in the field.