Biostatistics
Biostatistics applies statistical reasoning to biological, clinical and public-health data so observations can be summarized, uncertainty quantified and research questions answered.
General subject summary is free to everyone.
Biostatistics
Subject Summary
The public overview below follows the supplied PhysioVeda Academics subject summary.
Biostatistics applies statistical reasoning to biological, clinical and public-health data so that observations can be summarized, uncertainty quantified and research questions answered.
Good analysis begins by identifying the study population, variable type, measurement scale, design and whether data are independent or paired.
Descriptive statistics summarize the sample, while inferential statistics estimate population quantities and test hypotheses with explicit assumptions and uncertainty.
Statistical significance is not the same as clinical importance; effect size, confidence intervals, measurement quality and study design must be interpreted together.
This summary follows the uploaded PhysioVeda Academics outline from data types and descriptive statistics through probability, hypothesis testing, regression, diagnostic-test statistics, reliability, survival analysis and transparent reporting.
Whole-subject high-yield numbers
Use these supplied values and key facts for quick whole-subject revision.
| Item | Number / key fact |
|---|---|
| Mean | Sum of values / n |
| Variance | Average squared deviation from mean; sample variance uses n-1 |
| Standard deviation | Square root of variance |
| Standard error of mean | SD / sqrt(n) |
| 95% CI, large-sample mean | Estimate ± about 1.96 × SE |
| Type I error | Rejecting a true null hypothesis; probability = alpha |
| Type II error | Failing to reject a false null; probability = beta |
| Power | 1 - beta |
| Sensitivity | TP / (TP + FN) |
| Specificity | TN / (TN + FP) |
| Positive likelihood ratio | Sensitivity / (1 - specificity) |
| Negative likelihood ratio | (1 - sensitivity) / specificity |
| Risk ratio | Risk in exposed / risk in unexposed |
| NNT | 1 / absolute risk reduction, using proportions |
Core references
- Rosner B. Fundamentals of Biostatistics. 9th ed. Cengage; 2022.
- Daniel WW, Cross CL. Biostatistics: A Foundation for Analysis in the Health Sciences. 11th ed. Wiley; 2018.
- Altman DG. Practical Statistics for Medical Research. Chapman & Hall/CRC; 1991.
- Motulsky H. Intuitive Biostatistics. 4th ed. Oxford University Press; 2018.
Want to go deeper into Biostatistics?
Continue into the complete topic and subtopic learning system with structured summaries, medical visuals, topic wise OBQ practice, timed tests, explanations and results.