https://studiegids.vu.nl/en/courses/2025-2026/W_JSM_107Knowledge of statistics is crucial for performing empirical research and for understanding the academic literature related to PPE. The objective of this course is to provide students with the essential knowledge of statistics and to introduce them to the basics of econometrics. The course also provides essential tools for carrying out practical research, as part of the next years in the curriculum. Specific learning outcomes upon completion of this course are:Understanding of key concepts in probability theory and statisticsKnowledge of basic statistical/econometric techniquesAbility to interpret descriptive statistics and results of statistical, econometric and experimental analyses; understanding what conclusions can and cannot be drawn from such analysesUnderstanding the difference between correlation and causationAbility to formulate a regression model and estimate its parameters to answer a quantitative research questionAbility to perform simple analysis using statistical softwareThis course familiarizes PPE-students with both the theory and practice of statistics. They will be trained in formulating a research question into a model specification and in translating empirical results into policy recommendations, skills that are valuable both in PPE-studies and thereafter. The course starts with discussing key concepts in probability theory and statistics, like distributions, expectation and variance. Building on that, the students learn about estimating parameters, confidence intervals, testing hypotheses and the interpretation of significance. The second part of the course provides an introduction to econometrics. The most frequently used econometric technique is studied: the linear regression model. It is shown how different types of variables can be included in these models, in particular dummy variables. Special attention is given to the interpretation of the model parameters, whereby we distinguish correlation from causation and discuss omitted variables and multicollinearity. The latter issues are important for drawing conclusions and making policy recommendations based on empirical analyses. Throughout the course, the theory will be applied to real data using the statistical programming language R in a series of problem sets.Lectures, seminars and computer seminars. Please note that participation in the seminars and computer seminars is mandatory.Written exam (assessment of learning objects 1,2,3,4,5) (70%) Software exam (assessment of learning objects 1,2,3,4,5,6) (30%)An Introduction to Statistical Methods & Data Analysis. Seventh Edition. R. Lyman Ott & Michael Longnecker, Cengage.First year PPE studentsStatistical analyses are conducted in R (RStudio). During the computer tutorials, you must bring a laptop with RStudio installed and running (instructions will be provided). During the digital exams, we will use the VU-computers, which are Windows-based in English.