Introduction
This topic introduces biostatistics as the tool that turns medical observations into reliable conclusions. It covers the definition and aims of biostatistics, how a research programme and plan are built before any data are collected, and how variables are classified, with the four scales of measurement that decide which summaries and tests are allowed later.
Definition of biostatistics
Biostatistics is the application of statistical methods to data from biology and medicine. It covers the whole cycle of a study: planning, collecting, organising, summarising, analysing, interpreting and presenting data. Its purpose is to separate real effects from chance variation, so that clinical and public health decisions rest on evidence rather than impressions.
- Descriptive statistics summarise what was observed: averages, spread, proportions and tables or graphs.
- Inferential statistics use a sample to draw conclusions about a wider population, with estimates of uncertainty such as confidence intervals and tests of hypotheses.
- Typical medical uses include describing disease occurrence, comparing treatments, estimating risk factors, and evaluating diagnostic tests.