No prerequisites

1. Understand the basic concepts of population, sample, variable and statistic. 2. Know how to summarize a sample using measures of centre and variability. 3. Learn how to use statistical graphs to illustrate the main features of a sample. 4. Understand and implement the basic ideas of a regression analysis. 5. Learn how to estimate a population parameter based on sample data and how to formalize a hypothesis test. 6. Use of statistical software. 1. Capacity of analysis and synthesis. 2. Understanding of how to use computer packages. 3. Problem solving. 4. Teamwork. 5. Critical reasoning. 6. Verbal and written communication.

K3: Explain the main techniques of historical research, pointing out the importance of critical analysis of primary and secondary sources and recognize the main political and philosophical theories from Plato to contemporary debates on democracy, justice and power K9: Be able to debate and formulate critical reasoning, using precise terminology and specialized resources, on international and global phenomena, using both the concepts and knowledge of the different disciplines and the methodologies of analysis, paradigms and concepts of the Humanities and Social Sciences S2: Apply logical and creative thinking in solving complex historiographical and political problems S3: Experiment with research methodologies, simulating historical or political situations relevant to their analysis S10: Plan and organize teamwork by making the right decisions based on available information and gathering data in digital environments C1: Have critical and analytical skills evaluating historical sources and political texts to interpret their relevance in real contexts C2: Solve complex problems by adapting historical and political knowledge to propose effective solutions in contemporary situations C4: Demonstrate the ability to integrate theoretical knowledge into practical scenarios such as public policy analysis or historical-cultural projects

1. Introduction. 1.1. Concept and uses of statistics. 1.2. Statistical terminology. 1.3. Typos of variables. 2. Analysis of univariate data. 2.1. Representations and plots of qualitative data. 2.2. Representations and plots of quantitative data. 2.3. Numerical summary of a sample of data. 3. Analysis of bivariate data. 3.1. Representations and plots of qualitative and discrete data. 3.2. Representations and numerical summaries of quantitative data: correlation and regression. 3.3. Time series. 4. Probability and probabilistic models. 4.1. Random experiments, sample space, elementary and composite events. 4.2. Properties of probability. 4.3. Conditional probability and its properties. 4.4. Random variables and their characteristics. 4.5. Bernoulli trials and related distributions. 4.6. The normal distribution. 5. Introduction to statistical inference. 5.1. Outline and objectives. 5.2. Point estimators. 5.3. Interval estimators. 5.4. Fundamentals of hypothesis testing. 5.5. Tests for normal means. 5.6. Tests for proportions.

Theory (4ECTS). Theory classes with materials available on the web. Prácticas (2ECTS) Problem classes. Computing classes using statistical software. Group tutorials for resolution of problems, doubts etc.