BP201T · Semester 2 · B.Pharm
Unit III — Sampling & Statistical Inference
Applied Biostatistics and Data Analytics for Pharmaceutical Sciences
This study page introduces Sampling & Statistical Inference in Applied Biostatistics and Data Analytics for Pharmaceutical Sciences (BP201T), B.Pharm Semester 2. Read the selected definitions and short notes below, then download the full unit PDF.
Topics in this unit
- Population, sample, clinical-research sampling techniques, sampling error, and bias
- Central Limit Theorem
- Confidence intervals and interpretation
- Null and alternative hypotheses, Type I/II errors, p-values, significance, and Python calculation with pharmaceutical data
Definitions and short notes
Selected extracts from this unit’s notes. Download the full PDF below for the remaining topics and examples.
Population vs sample
Population = every member of the group you want to learn about (e.g., all diabetic patients in India). Sample = the smaller group you actually study (e.g., 200 patients in one trial). Parameter = a number describing the population (usually unknown, written with Greek letters like μ). Statistic = a number describing the sample (known, written with Latin letters like x̄ ) — used to estimate the parameter.
Unit PDF · page 2
Download notes
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For education and exam preparation only, not medical advice or current regulatory guidance.