Advanced Statistics

Company Name: EXIM Bank

Date: 15th Jan, 2018 - 01st Mar, 2018

Mode: Full time (1.5 hours everyday)

Course Content

Module 1 – “Business Statistics”

List of Topics

  1. Random variables. 
    • What is a random variable and what are its various types? 
    • What is a probability density function? 
    • How to model rare events and waiting time between events? 
  2. Jointly distributed random variables. 
    • How to determine relationships between variables?  
    • How to distinguish between conditional and unconditional expectation and  variances? 
  3. Elements of hypothesis testing. 
    • What is a hypothesis? How do you test the same? 
    • What is a test statistic?
    • What are confidence intervals?

The key learning outcomes from this program will be – 

  • Acquire a solid foundation in probability and statistics
  • Apply tools and techniques to understanding econometrics and advanced econometrics

Module 2 – “Econometrics for Business”

This course will build on the “Business Statistics course” and will address the following topics 

  1. Two variable regression 
    • What is a dependent and an explanatory variable? 
    • How to distinguish between an estimator and an estimate? 
    • What is the best linear unbiased estimator?  
  2. Multiple Regression Model 
    • How to model relationships when dependent variable depends on more than 1  explanatory variable? 
    • How to remedy the failure of classical assumptions such as multicollinearity,  autocorrelation, heteroskedasticity and selection bias? 
  3. Logit and Probit models 
    • How to model situations when the dependent variable is binary or qualitative?  • How to apply these models to business situations? 

The key learning outcomes from this program will be – 

  • Learn to formulate a model, estimate the same, and test hypotheses based on economic  theories. 
  • Fit an econometric model to real-world data, remedy the problems faced therein
  • Handle binary dependent variables in a logistic regression framework
  • Use the statistical environment “R” to estimate econometric models and analyse a variety of complex real-world problems. 

Module 3 – “Advanced Econometrics”

This course will build on the “Econometrics for Business” and will address the following topics 

  1. Endogeneity: Omitted variable bias, Measurement error, Simultaneity
    • How to remedy the above problems in the case of a multiple linear regressions as  well as structural equation modelling? 
  2. Instrumental variables: 2SLS
    • What is an instrument and how does it help when the explanatory variable is  correlated with the error term?
    • How to carry out estimation using instrumental variables? 
  3. Applied Time Series Forecasting with AR, MA, ARIMA models
    • How to forecast macroeconomic variables using simple time series models
  4. Volatility modelling with ARCH/GARCH models.
    • How is volatility modelled and forecasted in financial markets? 

The key learning outcomes from this program will be –

  • Impart necessary skills to model and forecast time series and cross-sectional data
  • Emphasise on empirical implementation strategies using extensive business applications
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