Course Outline


General Econometrics Concept

  • Understanding the basic concepts of Econometrics
  • Understanding variables and measures
  • Overview of probability and confident level
  • Statistical interference and percentiles
  • Theoretical probability distributions
  • Significance test and confidence interval method
  • Working with Asymmetry
  • Kurtosis
  • Anova

Regression Analysis

  • Concepts of regression
  • Understanding linear regression
  • Regression estimation
  • Regression interference
  • Understanding statistical assumptions
  • Violation of assumptions and implications testing
  • Understanding spurious regression
  • Understanding regression models
  • Transforming variables
  • Interpreting coefficients
  • Linear and non-linear regression models

Time Series Analysis

  • Components of time series
  • Different decomposition methods
  • Understanding trends, cycles, and seasonality
  • Performing stationarity tests
  • Interpreting graphs and correlogram
  • Performing unit root test
  • Transforming non-stationary time series
  • Stationary processes
  • Understanding complex transformations in the model
  • Economic and time series forecasting

Neural Networks

  • Understanding neural network concepts and methodology
  • Neural network composition
  • Overview of machine learning
  • Supervised vs. unsupervised learning
  • Machine learning vs. econometrics

Financial Risk Modeling

  • Measuring risks
  • Occurrence probability
  • Understanding the coefficient of variation
  • Risk adjustment capital

Markov Chain and Montecarlo Simulation

  • Understanding the concept of simulation and model
  • Distribution of fits and probability
  • Creating profiles
  • Random and outcome variables

Evaluating a Project

  • Defining project selection criteria
  • Understanding the elasticity of demand
  • Project economic feasibility
  • Risk breakeven analysis
  • Understanding the net flow
  • Using analytical tools
  • Stress analysis

Summary and Next Steps


  • Basic understanding of econometrics


  • Economists
  • Statisticians
  21 Hours


Related Courses

Statistical and Econometric Modelling

  21 hours

Statistical Analysis using SPSS

  21 hours

HR Analytics for Public Organisations

  14 hours

Talent Acquisition Analytics

  14 hours

R for Data Analysis and Research

  7 hours

Analysing Financial Data in Excel

  14 hours

Excel For Statistical Data Analysis

  14 hours

Statistics Level 1

  14 hours

Statistics Level 2

  28 hours

Minitab for Statistical Data Analysis

  14 hours

Statistics for Researchers

  35 hours

Forecasting with R

  14 hours

Statistics with SPSS Predictive Analytics Software

  14 hours

Advanced Statistics using SPSS Predictive Analytics Software

  28 hours

Administrator Training for Apache Hadoop

  35 hours