IIT JAM MS Programme is the postgraduate statistics program taught by IIT. The IIT JAM MS Entrance Examination is held from January - February(the time is not fixed for next year due to COVID-19).
IIT JAM MS Examination entirely focuseses on Objective Problems.
The exam scoring pattern is the following:
Let me discuss a little bit about the syllabus.
The Mathematics part involves
The Broad Topics in Proabability and Statistics are
I know you are waiting for this part. The truth is that, yes you can prepare yourself alone if you are enough motivated about solving problems on chance and data.
But the main problem is people don't know where to start. I will try to help you do so, in this post.
What will be my Focus?
Here, focus means with respect to your content. You have to be fully focussed on a single source for learning your topics. The best source is a book, where you can get it all. The easiest way in this information-rich world is to get lost. So, try to focus.
I always referred myself two books and therefore I recommend you to do so.
Just take this as the bible and you will do wonders. I can't guarantee you a position in the IIT JAM MS Statistics program, but I can guarantee you an enjoyable process of learning chance and data, which will put you in the top 10% of those in the preparation. The rest is left to luck.
For the Mathematics, portion be fluent in your 10+2 syllabus of mathematics and have a sound knowledge in Calculus and Linear Algebra.
I believe that majority are in this window. So, I strictly against any windowless than six months for the beginning of your preparation. It shows your attitude towards life and even if you get into IIT, it will cost you big somewhere in your life. So, stop procrastinating. Don't believe in that stuff that procrastinating makes you creative. That's a myth.
All the best!

Suppose, you get into ISI / IIT or don't get into ISI / IIT after your years of hard work. We believe, that you shouldn't work hard. Working hard means, you are doing something hard against something. You are in this path of study, only because you are in love with data. Even if you are not, then try to fall in love with the path of learning and crunching information from data. We are there to help you.
Cheenta will just help you organize your study program. We will ensure that you are on the right track and don't get off track with so much information out there. We give you a study plan, which will help you complete the tasks one step at a time. We will discuss problems from past years in accordance with the theory.
Above all, we will help you to learn the applications of data and the theory you are learning. We believe, statistics and data science without applications is as boring as a kite without the thread.
So, with every bit of knowledge you gain, we will teach you the coding perspective of it.
For example You are learning Probability 1 in our curriculum and you are introduced to the idea of equally likely sampling/selection. Now the natural question comes, how do I select equally likely objects by a machine? It is just a simple line of code.
sample(10,2)
5 8
From, this will arise questions, does this give equally likely in both the steps or it is SRSWOR? Our curriculum is based on the principles of ancient india. We are all seekers. We seek more and more. That is the moto of Cheenta.
If you believe, you can do these by yourself, you can do self study, rather than joining our program. You will get much more freedom.
For more information about our coursework, you can click here.
All the best.
Stay Tuned! Stay Blessed!
This problem is a very easy and cute problem of probability from ISI MStat PSA 2019 Problem 18.
Draw one observation \(N\) at random from the set \(\{1,2, \ldots, 100\}\). What is the probability that the last digit of \(N^{2}\) is \(1\)?
Last Digit of Natural Numbers
Basic Probability Theory
Combinatorics
Answer: is \(\frac{1}{5}\)
ISI MStat 2019 PSA Problem Number 18
A First Course in Probability by Sheldon Ross
Try to formulate the sample space. Observe that the sample space is not dependent on the number itself rather only on the last digits of the number \(N\).
Also, observe that the number of integers in \(\{1,2, \ldots, 100\}\) is uniformly distributed over the last digits. So the sample space can be taken as \(\{0,1,2, \ldots, 9\}\). So, the number of elements in the sample space is \(10\).
See the Food for Thought!
This step is easy.
Find out the cases for which \(N^2\) gives 1 as the last digit. Use the reduced last digit sample space.
So, there are 2 possible cases out of 10.
Therefore the probability = \( \frac{2}{10} = \frac{1}{5}\).
