Objectives
The course, through lectures and computer lab sessions, aims to illustrate the fun-daments of statistical modeling with multiple covariates focusing on the linear and Objectives
The course, through lectures and computer lab sessions, aims to provide basics notions of statistics to plan and analyze the results of a scientific study or experi-ment.
At the end of the course the participants should be able to choose the most suit-able design for their study, compute the optimal sample size, perform a graphical and tabular description of the data collected and analyze the association between variables through proper measures and hypothesis testing.

Course program
Day 1:

• Planning a study: types of designs
• Data summaries: descriptive measures and graphical representa-tions.
• Lab session with R
  Day 2:
• Introduction to hypothesis testing
• Parametric tests for quantitative variables
• Lab session with R
  Day 3:
• Non-parametric tests for quantitative variables
• Tests for categorical variables
• Lab session with R
  Day 4:
• Correction for multiple comparisons
• Sensitivity, specificity and Lab session with R

Target audicence
Doctoral students of any discipline who are interested in the practical application of basic statistical methods for data analysis in scientific research

Participants
Min 20 Max 40