Introduction to Biostatistics and Epidemiology

Vocabulary flashcards that cover the fundamental terms introduced in the lecture on biostatistics and epidemiology.

Biostatistics

The branch of statistics that interprets scientific data generated in biology, public health, and medicine.

Descriptive Biostatistics

Area of biostatistics that summarizes data using numbers and graphs, such as means, medians, and frequencies.

Inferential Biostatistics

Area of biostatistics that draws conclusions or makes predictions about a population using probability, hypothesis testing, and confidence intervals.

Epidemiology

The study of the distribution and determinants of health-related states or events in specified populations and the application of this study to control health problems.

Distribution (Epidemiology)

The frequency and pattern (who, when, where) of health events in a population.

Determinants

Biological, behavioral, environmental, or social factors that influence the occurrence of health problems.

Outcomes

Health results such as morbidity, mortality, or recovery that epidemiologists measure.

Population-based Approach

Perspective in which groups—not individuals—are the primary unit of analysis in epidemiology.

Application (Epidemiology)

Use of epidemiologic findings to prevent new cases, control existing problems, and inform health policy and programs.

Descriptive Epidemiology

Branch of epidemiology that describes disease occurrence by person, place, and time.

Analytic Epidemiology

Branch that examines causes and associations using study designs like case-control, cohort, and experimental studies.

Applied Epidemiology

Use of epidemiologic data to implement and evaluate public-health interventions.

Quantitative Data

Numerical data that can be measured or counted.

Discrete Data

Quantitative data consisting of countable, finite values (e.g., number of red blood cells per mm³).

Continuous Data

Quantitative data that can take any value within a range (e.g., weight, serum cholesterol).

Qualitative Data

Categorical data that describe attributes or characteristics rather than numerical values.

Nominal Data

Qualitative categories with no inherent order (e.g., blood type).

Ordinal Data

Qualitative categories with a specific order but unequal intervals (e.g., tumor stages I–IV).

Independent Variable

Variable that is manipulated or categorized to examine its effect on an outcome (e.g., smoking status).

Dependent Variable

Outcome being measured in a study (e.g., lung cancer incidence).

Confounding Variable

Factor associated with both the exposure and the outcome, potentially distorting their relationship (e.g., age in a smoking study).

Controlled Variable

Variable kept constant to prevent it from influencing the study outcome (e.g., lab temperature).

Nominal Scale

Level of measurement with categories that have no order; analysis often uses frequency and mode.

Ordinal Scale

Level of measurement with ordered categories and unequal intervals; median and non-parametric tests apply.

Interval Scale

Ordered scale with equal intervals but no true zero (e.g., temperature in °C); allows means and standard deviations.

Ratio Scale

Interval scale with an absolute zero point (e.g., weight, age); permits all statistical operations.

Incidence Rate

Number of new cases of a disease occurring in a specified population during a defined time period.

Prevalence

Total number of existing (often active) cases of a disease in a population at a given point or period in time.

Case Fatality Rate (CFR)

Proportion of deaths among confirmed cases of a given disease, expressed as a percentage.

Reproductive Number (R0)

Average number of secondary infections produced by a single infected individual in a susceptible population.

Morbidity

The state of illness or the incidence of disease in a population.

Mortality

Incidence of death in a population.

Recovery

Return to health after illness; one of the possible outcomes measured in epidemiology.