1. Diagonal Matrix A diagonal matrix is a square matrix where all elements outside the main diagonal are zero. For
Definition of a Matrix A matrix is a rectangular array of numbers or symbols arranged in rows and columns. Matrices
I have not experienced such wonderful training in my journey so far either in Pharma or in CRO. The training was absolutely superb and I thoroughly enjoyed each and every day’s session. The content was extremely informative with the right mix of theory and practical, along with exercises and supplied R codes. I have attended several trainings before but I can’t recall any of them having such a strong impact on me. Overall it is much more than my expectations.
This was a highly interactive course with an expert in Bayesian Statistics who provided a very interesting and detailed introduction to the subject. I really appreciate and like the step by step approach adopted by Sir to introduce Bayesian Statistics. The progression of the course was very smooth. The detailed theoretical explanation of the concepts and their implementation through an example was a perfect combination. The course helped me understand different approaches in statistics and provided hands-on experience in using R software (R stan). It was beyond my expectations.
First of all, thank you so much for organizing such wonderful Bayesian statistics training. I totally enjoyed last 10 days and learned a new thing in a comfortable environment. The knowledge of the trainer was totally amazing. It was big opportunity to me to familiar with Bayesian Statistics and R software. Lots of things I learned from this training. Since this Bayesian statistics is complex topic, so I need to do more practice to gain the complete picture of Bayesian theory and implementation. And this training will help me to improve my knowledge.
It was a very well structured and delivered training program. The explanations were generally easy to follow and reproduce. Highly enjoyable and instructive. Assignments were all relevant. This training took me from brief to advance level concepts of bayesian statistics and methods. For eg: The MCMC session, it helped my understanding if we had to fit a Bayesian model to a dataset from scratch with our own implementation. This was definitely not an easy topic. But the learning was immense.
Initial day training on the introduction of Bayesian concept was in detailed and easy to understand. The way, the trainer explained each concept in this 2 weeks was in detailed and understandable. The study materials that were shared are also good. I enjoyed and greatly benefited from the whole session.
Firstly, thank you so much for arranging such a great and engaging session. Please find the following feedback of Bayesian Training. This course is extremely useful. Trainer did a nice job of explaining complicated topics and the practice was key to understanding. Trainer was very much patient and amazing. Extremely impressive, efficient and a very good communicator. Material was very good. He really enhanced the content and made the two weeks enjoyable. I really appreciate the trainer the way he was repeating the concepts, definition, and exercises into the ongoing training.
Firstly, thank you for organizing such a knowledge session. Here is my feedback on the whole training. Bayesian Analysis being relatively new topic for me, I felt that the basics were very well covered that helped to understand the more complex problem that were discussed later in the session. The flow of the topic was especially good. One thing that was intriguing was the fact that I understood that 2 different methods may not always lead to mathematically different solutions. It is the change in the approach that makes classical and a Bayesian school of thought different. Easy to understand materials were shared after each session, that further helped to clarify the doubts. The codes discussed and shared in the session helped to understand Rstan more effectively. Will surely go through the materials, recorded sessions to gain further proficiency. Enjoyed the last two weeks thoroughly.
I found the 10 days training to be very informative and brainstorming. The way of teaching and explaining of the Dr. Subbiah sir was very unique. It was great opportunity for us to gain more and deep knowledge of Bayesian theory and implementation. Many of new things I learn from this training, especially for rstan is a new tool I learnt from this training. Now a days very few organizations are started using the Bayesian statistics implementation and we are the one of them. Though Bayesian is not very easy to learn and understand, we need to do more practice. And this training will help me to improve my knowledge. Again many thanks to you for organizing such great platform for us!
Apologies for not being so interactive during the sessions. I want to thank you for arranging such a wonderful training session for us. The training was really great, especially the tasks that were provided by the trainer were helpful to understand the topic more precisely. I will not say that I have understood each and every thing but I sincerely tried to understand as much as possible. Further research and study need to be done by me to understand the topic more extensively.
First of all I would like to thank you for organizing an amazing training session. Not only the training session was very informative and also the material that was provided at end of the each day from Day 1 to Day 10 which was very useful. What I have enjoyed the most was hands on training using Rstudio and Rstan which really helps to understand the concepts. Also the trainer was excellent, well informed and helpful.
I have the following feedback on the training
Overall experience: Hoping this training could act as a prior if there is any likelihood of Bayesian related work arises, where it will make a positive impact on the posterior deliverables!
The content: the training started from basic and covered advanced topics on Bayesian.
The flow: Along with the content the flow of covering these was also very good
Training style: although being virtual, it was pretty good. The efforts those were put by him to make the training more interactive is commendable.
Materials: Awesome.
The Workshop was well organised with technically informative sessions by Dr.M.Subbiah… This workshop made a starter for us to learn R and definitely an initiative to work with projects.
Two Weeks International FDP On Research Tools 2023, Department of Artificial Intelligence and Data ScienceEaswari Engineering College(Autonomous), Chennai
“Hands-on, interactive, and deeply insightful—ideal for both students and professionals.”
“The sessions enhanced our statistical thinking and helped us apply concepts confidently in real-world problems.”
“From Bayesian inference to applied analytics, the teaching was clear, engaging, and industry-relevant.”
“A learning experience that built confidence, clarity, and strong analytical foundations.”
“The structured approach and real examples made even complex topics easy to grasp.”
This is to certify that I have been privileged to closely collaborate with Dr M Subbiah for the past five years… I have no hesitation in strongly recommending Dr. M. Subbiah for research and teaching assignments.
This is to certify that Dr M Subbiah is known for me over a decade as a Mathematics teacher, and a doctoral student of mine… He is an acknowledged teacher and has been teaching courses like Mathematical Statistics, Statistical Inference, and Generalized Linear Models.
I have worked with Subbiah sir as an intern as well as in 6 month project thesis. In both the projects which I worked with him, an important skill I learn is that sir makes sure before we start working on it he makes sure we plan on what we do before going to start the project… This aspect has helped me in writing my Actuarial exams as well in my job which I am doing.
Sir,
I have done three projects under your guidance. I had first hand research experience due to those projects. My interest on Bayesian Inference started to build up and I learnt so many new things that is essential for further education. Your continuous support, guidance and inspiration helped me to form innovative ideas and ultimately gave me the self confidence and determination to pursue a research career. Whatever I have learnt, whatever I am doing, all credit goes to you. As your student, I am grateful to you. I feel lucky. I wish I could learn more from you. I hope, I will have that opportunity again in future.
Worked on project and gained hands on experience on handling data and learning how to use appropriate statistical methods in data analysis. With the enough guidance, I am now associated with an internship in Actuarial Firm.
I have taken a course on Bayesian inference & worked on a technical report. Their teaching & valuable guidance inspired me to pursue higher studies. It was a wonderful experience to work under them.
I have worked on a technical report & the unique way of teaching enhanced my statistical thinking. It helped me to think dynamically and explore various perspectives of Statistics. Their guidance inspired me to pursue my higher studies.
I have done 2 projects & internship under their guidance. Teaching, & interactive class helped for my higher studies. Looking more opportunities to work with them.
I have done three projects under their guidance. The continuous support, and inspiration helped me to get confidence and determination.
Zero correction is a common method that we are using to estimate Odds ratio in the presence of zero cells. The paper ‘Classification of 2×2 sparse data sets with zero cells’ by Subbiah M et al. (2008) in Statistics & Probability Letters, was very much helpful to understand in what and all situations we can really adopt the method of zero correction to estimate the OR.
I got an opportunity to refer the article entitled on “Classification of 2×2 sparse data sets with zero cells” published on Statistics and Probability Letters (2008) which was useful for me to assess and understand the degree of sparseness in our study data. Based on that, we applied penalized likelihood logistic regression method for odds ratio since the severity level on sparseness in my dataset was huge. I personally thank them for publishing this valuable article and I appreciate the work on the topic.
Dr.Subbiah gave an invited talk in GSK Bangalore addressing the Statisticians working in the Development of Pharma and Vaccine Business units. He primarily focused on Bayesian thinking and its motivation, necessarily the differences between the frequentist and Bayesian methods. On behalf of everyone at Clinical Statistics, GSK, Bangalore, we would like to thank Dr.Subbiah for the amazing presentation and his delivery was exemplary. By combining humour, examples, and an informal but highly focused presentation, he demonstrated his command of communication principles and gave his audience immediately useful take-away. The audience left feeling excited and motivated. I would strongly recommend them for any future event, either inside or outside of our company.