Introduction to Biostatistics - Lecture 1
Course Overview
- Main Aim: Understanding statistics and biostatistics.
- Course Materials:
- "Introduction to Probability and Statistics" by Mendenhall, Beaver, and Beaver.
- "Introduction to Probability and Statistics for Engineers and Scientists".
What is Statistics?
- Science dealing with the collection, classification, analysis, and interpretation of numerical data.
- Examples:
- Elections: Opinion polls predicting outcomes.
- Weather Patterns: Predictions impacting government decisions.
- Income by Profession: Understanding income trajectories in various fields.
What is Biostatistics?
- Application of statistics to biology.
- Examples:
- Evolution: Analyzing structural changes over time.
- Medicine: Predicting drug resistance.
- Public Health: Managing disease outbreaks like the Zika virus.
History of Statistics
- Originated from gambling studies.
- Developed through works of DeMoyver, Laplace, Galton, Carl Pearson.
- Importance in biology and clinical sciences.
Importance of Studying Statistics
- Clinical Trials: Designing trials, understanding stopping protocols.
- Cell Motility: Measuring effects of drugs on cell movement.
- Protein Folding: Measuring forces for unfolding proteins, understanding distribution.
Types of Studies in Statistics
- Surveys/Cross-sectional Studies: Collecting current data.
- Retrospective Studies: Analyzing past data.
- Prospective Studies: Long-term tracking of population.
- Clinical Trials: Testing safety and efficacy of drugs.
Sampling Techniques
- Simple Random Sampling: Unbiased selection from a population.
- Systemic Sampling: Selecting at regular intervals from a list.
- Stratified Random Sampling: Sampling in proportion to sub-populations.
Examples of Statistical Techniques
- Random Sampling Example: Selecting combinations from a set.
- Polling Example: Importance of accurate sampling to avoid incorrect predictions.
Conclusion and Next Steps
- Summary: Overview of statistics and biostatistics, examples, and sampling methods.
- Next Lecture: Focus on measuring numbers from experiments, creating understandable plots from data.
- Homework: MCQs for review and understanding of today's lecture.
Thank you for attending the first lecture. Please review the MCQs to reinforce your understanding of the material covered.