This comprehensive webinar is hosted through Zoom and runs over a total of 9 hours, with 4 hours each day (2 in the morning and 2 in the afternoon) with an extra Q&A session on the second day.
Regression modelling is a fundamental tool in the research box of every economist, econometrician or applied researcher in a variety of fileds. Regression refers to the set of models that capture the dynamics of the expected /average value of a variable of interest.
This course is for researchers from all academic disciplines who are new to Stata. The course assumes only limited statistical knowledge and experience of using statistical software. The participants will be introduced to Stata and will be taught the statistical theory behind linear and non-linear regression methods. These methods to specially chosen datasets using examples from macro economic and finance research.
Two days of online instruction for four hours per day.
Two hours each morning, followed by two hours each afternoon.
Hour-long Q&A session at the end of each day to address queries.
Session 1: Linear regression Part 1
- Getting started with Stata
- Importing data from other formats and writing coomand
- Regression models: why they are so important
- Setting up a linear regression: Interpretation, variable selection, estimation, dummy variables
Session 2: Is the Model good enough?
- Post –estimation diagnostic tests
- Serial correlation
- Non -linarites
- Structural Breaks
Session 1: Non-linear regression models
- Non linear Least Squares and MLE in Stata
- Interpretation of results
- Model diagnostics
- Which type of non –linear model?
Session 2: The power of non -linarites
- Short-comings of the linear model
- Model with regime switches
- Maximum likelihood estimation
- Markov chain models
- Exponential and other curve fittings Models
- No prior knowledge of Stata is assumed
- A good knowledge of hypothesis testing will be assumed.
- All costs exclude local taxes, where applicable.
- Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrollment).
- Additional discounts are available for multiple registrations.
- Payment of course fees required prior to the course start date.
- Registration closes 1 calendar day prior to the start of the course.
- 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
- 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
- No fee returned for cancellations made less than 14-calendar days prior to the start of the course.
The number of delegates is restricted. Please register early to guarantee your place.