Medical Statistics Collocations: Practical Medical English for Public Health
Overview
This resource focuses on common collocations—word combinations—used in medical statistics within public health contexts. It helps learners and professionals read, write, and communicate statistical findings clearly and accurately in English.
Who it’s for
- Public health students and researchers
- Clinicians interpreting epidemiological studies
- Translators and medical writers
- Non-native English speakers working with health data
Key sections
-
Basic statistical terms & collocations
- Examples: measure of association, confidence interval, statistical significance, p-value threshold, sample size calculation.
-
Epidemiology-specific phrases
- Examples: incidence rate, prevalence estimate, relative risk, adjusted odds ratio, attributable fraction.
-
Study design and reporting collocations
- Examples: cross-sectional study, case-control design, cohort follow-up, randomized controlled trial, intention-to-treat analysis.
-
Data analysis and interpretation phrases
- Examples: multivariable regression, model fit, sensitivity analysis, interaction term, statistical power.
-
Communication and writing collocations
- Examples: statistically significant, clinically meaningful, evidence suggests, results indicate, limitations include.
Learning features
- Collocations grouped by function (description, analysis, interpretation, reporting)
- Example sentences showing correct usage in abstracts and results sections
- Short exercises: complete-the-phrase, match collocation to definition, rewrite sentences using precise collocations
- Quick-reference cheat sheet for manuscript writing and presentations
Practical benefits
- Improves clarity and precision in reporting public health statistics
- Reduces ambiguity in interpreting study findings
- Speeds up manuscript preparation and peer review communication
Quick sample sentences
- “The adjusted odds ratio for exposure was 1.8 (95% confidence interval: 1.2–2.7), indicating a statistically significant association.”
- “We performed a sensitivity analysis to assess the robustness of the prevalence estimate.”
- “Sample size calculation was based on achieving 80% statistical power to detect a 10% difference.”