Probability Statistical Inference Programming in R Regression Models

CG1 Ability to apply analysis techniques with the aim to adapt the information to real problems. CG2 Ability to identify the best stochastic model for each real problem, and to apply it for its analysis, design and solution. CE5 Apply advanced statistical foundation for the development and analysis of real problems that include the prediction of a response variable. KNOWLEDGE ACQUISITION 1) Clinical Trials 2) Survival analysis 3) Models for longitudinal data and repeated measurements

1 Clinical Trials Data Analysis 1.1 Basic concepts 1.2 Treatment comparisons 1.3 Meta-analysis 2 Survival analysis 2.1 Basic concepts 2.2 Descriptive methods for survival data 2.3 Regression models for survival data 3 Models for longitudinal data and repeated mesurements 3.1 Hierarchical data 3.2 Models with random intercept and slope 3.3 Generalized Estimating equations

Learning activities: Master classes Exercises Computer labs Projects Teaching methodologies: Presentations of the professor in class with computing and visual media, where the professor develops the mail concepts of the subject and provides bibliography supplementing the knowledge of students. Critical reading