ADVANCED BIOSTATISTICS
- Course
- BIOT509 - ADVANCED BIOSTATISTICS
- Department
- Biotechnology - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 8
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- -
- Prerequisite
- -
Course Description
This course is designed for students to gain an understanding of statistical data analyses and experimental design in the field of biological sciences, including statistical analyses used in epidemiology. Practical and non-theoretical approaches to the statistical analyses of laboratory data is discussed; including experimental design, mistakes in experimental design, rigor and reproducibility and bias in scientific research. Topics and statistical tests such as hypothesis testing, T-tests, 1-Way and Multi-Way ANOVAs, post-hoc tests, correlations and regressions, non-parametric statistics, power analyses and dose-response analyses are presented with examples from several fields with an emphasis on biotechnology. Prism from GraphPad is introduced and used throughout the course, as well as SPSS. Literature from biotechnology research will be used to provide students examples of statistical analyses of real-life data.
ADVANCED BIOSTATISTICS
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Course outcomes
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Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Review of key statistical terms, Research methods in psychology, and general overview of SPSS. |
| Week 2 | Research Methods and Designs |
| Week 3 | Introduction to SPSS, establishing a data set, data entry, cleaning up the data set |
| Week 4 | Changing variables, Calculations |
| Week 5 | Frequencies, Descriptives, Graphs, Tables, Normal distributions |
| Week 6 | Inferential statistics, Introduction to hypothesis testing, parametric and non-parametric data |
| Week 7 | Midterm Exam |
| Week 8 | Chi-Square, Assumptions, Interpretation, and Write-up (APA format) |
| Week 9 | t-test (one sample, independent sample, paired sample) Assumptions, Interpretation, and Write-up (APA format) |
| Week 10 | One Way ANOVA and post-hoc analysis (parametric and non parametric) Assumptions, Interpretation, and Write-up (APA format) |
| Week 11 | Multiple ANOVA (MANOVA) Assumptions, Interpretation, and Write-up (APA format) |
| Week 12 | Correlation, Assumptions, Interpretation, and Write-up (APA format) |
| Week 13 | Regression Analysis, Assumptions, Interpretation, and Write-up (APA format) |
| Week 14 | Factor Analysis, Assumptions, Interpretation, and Write-up (APA format) |
| Week 15 | Final Exam |
Reference Books & Course Materials
- 01 Fundamentals of Biostatistics 8th Edition, Bernard Rosner
- 02 Biostatistics, A Foundation for Analysis in the Health Sciences 9th Edition, Wayne W. Daniel
- 03 Medical Statistics Made Easy, M. Harris and G. Taylor
Learning Outcomes
No learning outcomes have been defined.
Program Outcomes
- To work effectively as leaders and team members by applying technical expertise, scientific knowledge, and ethical principles in biotechnology.
- To plan, conduct, document, and communicate hypothesis-driven and laboratory-based research in biotechnology.
- To interpret and critically evaluate bioinformatics and genetic data generated from human research.
- To use and apply molecular, cellular, and genetic techniques in biotechnology research for medicine, health sciences, agriculture, and the food industry.
- To apply knowledge of the molecular and genetic mechanisms underlying human diseases in the evaluation of potential treatment approaches
- To interpret, synthesize, write, and communicate scientific information for both the scientific community and the general public.
- To provide training on the research, development, and production of products for biotechnology-related industrial fields in the public and private sector
- To apply ethical principles and professional responsibility in biotechnology research and practice.
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