1. Variability of Biological Phenomena and Measurement Errors 1.1. Phenotypic Variability 1.2. Temporal Variability. 1.3. Measurement - Related Variability 1.3.1. The Measurement 1.3.2. Measurement Errors 1.4. Variability of Diagnostic Tests Summary 2. Distinctive Aspects of a Biomedical Study. Observational and Experimental Studies 2.1. Distinctive Features of Biomedical Studies 2.2. The Study Protocol 2.3. Observational Studies 2.4. Experimental Studies Summary 3. Observational Studies 3.1. Basic Designs of Observational Studies 3.1.1. Prospective or Cohort Studies 3.1.2. Retrospective Studies or Control Cases 3.1.3. Sample Size 3.2. Bias and Confounding 3.2.1. Control of Bias in Epidemiology 3.2.2. Control of the Phenomenon of Confounding 3.3. Advantages and Disadvantages of the Different Types of Observational Studies Summary 4 Defining the Treatment Effect 4.1. From the Single Measurement to the Signal 4.2. Identification and Quantification of the End-Points (Individual Subject Level) 4.2.1. Methodological Characteristics of the End-Point 4.2.2 Discriminating Between Primary and Secondary End-Points and Between Efficacy and Safety/Tolerability End-Points 4.3. Identification and Quantification of the Signals (Group Level) 4.4. Statistical Considerations 4.5. Practical, Regulatory, Marketing and Pharmaco-Economic Considerations 4.6. Selection and Characterization of the Primary End-Point and Signal: an Example 4.6.1. Stage One: Define the Main Therapeutic Level 4.6.2. Stage Two: Define the Primary End-Point (Individual Patient Level) 4.6.3. Stages Three and Four: Define the Group Indicator, the Signal, and the Threshold of Clinical Relevance (Treatment Group and Study Levels) 4.7. More Than One Question in the Same Study: the Problem of Multiple Statistical Tests 4.8. Validation of Measurement Scales 4.9. Special Types of End-Points Summary 5. Probability, Inference and Decision Making 5.1. Probability 5.1.1 Definitions 5.1.2. Probability Distribution and Probability Density Function 5.1.3. Normal or Gaussian Distribution 5.2. Basic Concepts of Inference 5.2.1. Hypothesis Testing and Statistical Formulation of the Medical Question 5.2.2. Statistical Estimation as the Tool for Evaluation of Clinical Relevance 5.3. Statistical Inference in the Frequentist and the Bayesian Approaches 5.4. Two Digressions: Measures of Variability and Likelihood Function 5.4.1. Measures of Variability 5.4.2. Likelihood Function 5.5. Frequentist (Classical) Analysis of a Clinical Trial 5.5.1. Hypothesis Testing: the Frequentist Solution 5.5.2. Estimation of the Effect: the Frequentist Solution 5.6. Bayesian Analysis of a Clinical Trial 5.6.1. Hypothesis Testing: the Bayesian Solution 5.6.2. Estimation of the Effect: the Bayesian Solution 5.7. Some Additional Considerations on the Frequentist and Bayesian Approaches 5.8. Parametric and Non-Parametric Inference 5.9. Statistical Decision Making in the Medical Field 5.10. Evidence-Based Medicine Summary 6. The Choice of the Sample 6.1. Which Subjects Should Form the Sample? 6.1.1. Characteristics of the Patients to be Enrolled in the Study 6.1.2. Mechanism of Subject Selection 6.2. How Many Subjects Should Form the Sample? 6.2.1. Statistical Considerations 6.2.2. Medical and Practical Aspects Summary 7. The Choice of Treatments 7.1. Study Treatments 7.1.1. How Many Treatments 7.1.2. What Treatments 7.1.3. Blinding of the Study Treatments 7.1.4. Packaging and Logistics 7.2. Concomitant Treatments Summary 8. Experimental Design: Fallacy of 'Before-After' Compa