ECPHM Epidemiology and Statistics course

Friday, November 1, 2019 (All day)
WebEx Weblecture
Contact person: 
Education Committee



Epidemiology and Statistics course for ECPHM Residents; interactive weblectures by Marcus Doherr.

The ECPHM board and Education Committee are glad to announce the first interactive course on Epidemiology and Statistics.

The course consists of 8 modules that preferably are followed all consecutively. Individual modules will be recorded and become available in the resident forum section of the ECPHM website approximately 1 week after the weblecture.

Below all dates for the modules are listed. Residents will receive individual invitations in due time. However, please reserve the dates in your agenda already

For any further information, please contact the Education Committee.



Epi01 Diseases in populations

epidemiology, description of events over space & time

measures of morbidity (I, P) and mortality (M)

prevalence surveys with sample sizes

spread of disease, basics of SIR modelling



Epi02 Association studies

General principles if sample-based studies

Observational studies

Experimental studies

Measures of association (RR, OR)

Bias and confounding

Sample sizes for epidemiological studies



Epi03 Diagnostic tests

Objectives of diagnostic test evaluation

Sensitivity and Specificity

Gold standard, cutoff and ROC

Predictive values

Apparent and true prevalence

Aggregate testing, pool/herd approaches



Stat01 Objectives of statistics

Population parameter and sample estimate

normal and binomial disctribution

Basic descriptive statistics (central tendency, spread)

Reference values and confidence intervals



Stat02 Statistical hypothesis testing, alpha, beta, p-values

One and two sample tests (t, chiSquare)

Simple and 2-way ANOVA



Stat03 Correlation

simple linear regression

concept of multivariable models



Stat04 dependent / repeated measures statistics

survival data and related statistics (Kaplan Meier, Cox Regression)



Stat05 Count data (Poisson Regression)

Binary outcomes (Logistic Regression)



© 2021 ECPHM - Webdesign by