Enrolment options

  1. Basics on statistics and probability
    • Derivatives and integrals (revision)
    • Some basics on correlation and causation
    • Inferential statistics (population and sample, Weak Law of Large Numbers, Central Limit Theory)
    • Descriptive statistics (measures of central tendency, measures of variation, percentiles…)
    • Experiments, conditional probabilities, random variables, probability density functions for continuous and discrete random variables, characteristics of probability distributions
    • Introduction to estimation (unbiasedness, efficiency, consistency)
    • Exercises
  1. Introduction to econometrics
    • What is an econometric model? Variables, parameters
    • Linear models and basic assumptions
    • Exercises
  1. R coding
    • Installing R and Rstudio
    • R environment and packages
    • R coding (functions, vectors, dataframes)
    • Importing and exporting data
    • Data management
    • Basic data analysis
    • Graphics
    • Exercises

 

 

 

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