Dear Graduate students, I am very glad that you have decided to take this advanced statistical computional course, which is vital for your scientific carrier. As we all know the progress in science has been made by combining theoretical framework and practical observations in a very systematic and now a well established procedure. A theoretician usually describes a particular system under his or her investigation by introducing parameters that can suitably capture the desired properties of this system.
Very often it is hard to measure these theoretical and desired parameters directly. In fact we cannot determine exactly the values of any thing we can measure in someway; there is always unavoidable noise. Several researchers around the globe have developed an ingenious method of inferring theoretical parameters from other parameters that can be measured directly in the presence of noise, which can also in someway be related to the theoretical parameters.
In this course we shall explore these arsenals of tools and techniques systematically and build up your skills so that you can use them in various applications in your future research and development carriers. We shall start from a simple description of forward and inverse problem and then go on to the more advanced statistical computing and inference techniques including statistical Bayesian inversion, Monte Carlo simulation and Markov Chain Monte Carlo method.
You will be required to submit three major reports by carrying out an independent study on Bayesian inversion theory, Monte Carlo Simulation technique and Markov Chain Monte Carlo method. Your report should include clear theoretical investigations of these topics with practical demonstrations on how they can be used in various applications. The programs you have developed for such purpose should be included in the report. You will be required to present the three reports in public and defend them. A demonstartion of competence on theoretical understanding of these topics and also the ability to apply them in practice are essential to pass the course. There are many reference materials online and also in the Library of Engineering Faculty on measurement and estimation theory. GOOD LUCK WITH THIS EXCITING COURSE!!
Report writing instructions: All your reports should be written in Latex using the standard Physics Graduate Program latex style file. You must submit them electronically in PDF. If you do not have have earlier experience in how to use Latex please click HERE.
My lectures can be downloaded by clicking on the links below. I will try my best to make the lectures available in this site before class. There might be errors or misprint in the materials and please report them to me as you find one.
2. Module One
3. Click here to download one of the references for free
To see a report sample from previous year CLICK HERE and for sample class presentations CLICK HERE and sample Master theses can be found HERE.
To see a sample from International Refereed Journal Papers CLICK HERE
a sample poster can be found HERE