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
Introduction to econometrics
What is an econometric model? Variables, parameters
Linear models and basic assumptions
Exercises
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
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
Introduction to econometrics
What is an econometric model? Variables, parameters
