Data Science and Biotechnology
This cluster introduces foundational concepts in statistics, probability, and data science and demonstrates how they are applied in biotechnology. Through interactive learning experiences, students explore experimental design, data analysis, data visualization, clinical trials, artificial intelligence, machine learning, and evidence-based scientific reasoning in modern biological research.
Topics
- summary statistics
- probability
- bayes theorem
- sum rule
- product rule
- simpson's paradox
- positive control
- negative control
- placebo
- variable
- hypothesis
- research question
- bar graph
- line graph
- scatter plot
- histogram
- clinical trial
- artificial intelligence
- machine learning
- regression
- data science
- statistical analysis
- descriptive statistics
- inferential statistics
- statistical reasoning
- statistical literacy
- data interpretation
- data visualization
- graph interpretation
- quantitative reasoning
- probability theory
- conditional probability
- independent events
- sampling
- sample size
- bias
- correlation
- causation
- statistical significance
- uncertainty
- variability
- scientific method
- experimental methods
- controlled experiment
- control variables
- confounding variables
- randomization
- blinding
- study design
- randomized controlled trial
- evidence-based medicine
- epidemiology
- public health
- clinical research
- predictive modeling
- classification
- supervised learning
- algorithm
- AI literacy
- responsible AI
- computational thinking
- data-driven decision making