# IISc MTech (Research) Interview Experience (CSA)

*21 May 2019*

*Gate score* - 762, *AIR*- 388, *Category* - General

In CSA dept, there are 3 areas to choose from, in which we want to be interviewed. This form we had got well before the interview. They were Theory, Systems and Intelligent systems. Also the subjects to prepare in these areas were given in the form. I had chosen Intelligent systems. Test was different for different areas. I felt written test was a bit tricky, there were 2-3 questions on Vector spaces and Orthogonal spaces which I couldn’t solve. The programming and Algo questions were easy, we had to arrange the functions in increasing time complexity. Then there were questions from Probability and Combinatorics. My test went ok, so I didn’t had much hopes to get shortlisted for interviews.

However I was called for the interviews. The interviews were going on for just 15-20 mins. And I was the 4th one to be called. So at around 4:00pm, my turn came.

**Interviewer**: *(Read out my entire profile. Asked where did I work before what was the profile but not much on that)*. So what have you prepared?

**Me**: Sir Probabilty and Linear Algebra. *(And they just asked me questions on Probability in entire interview)*

**Interviewer**: Do you know what is Normal distribution? Write it on board

**Me**: I wrote the definition of PDF of Normal distribution.

**Interviewer** : What does this function represent?

**Me**: Sir, the area under the curve gives the probability for the x values in given range.

**Interviewer** : Show how it denotes the area under range

**Me**: I tried explaining it with the figure, but they snapped me saying we all are grown ups and don’t draw figures. Then I wrote it as \(P(a<=x<=b)\) and maybe they wanted this.

**Interviewer**: What is CDF?

**Me**: Explained

**Interviewer**: How do we get CDF from PDF?

**Me**: By integrating the PDF we will get the CDF sir.

**Interviewer**: Write the CDF of Gaussian distribution

**Me**: I wrote the definition using integration

**Interviewer**: Then they asked what is CDF for uniform distribution

**Me**: I wrote that.

**Interviewer**: Then they gave 2 Random variables, \(U1\), \(U2\), which are having Uniform distribution, if \(Z\) is another random variable such that, \(Z=max(U1,U2)\), what will be the CDF for \(Z\)?

**Me**: I wrote Z as they had defined. But was clueless how max will work and how will \(Z\) look *(2-3 minutes went here, I was struggling, there were CDF for unifrom distribution on board and I had to link it to get CDF for Z, I was trying to explain them my approach)*

**Interviewer**: Gave some hints

**Me**: Unable to join the dots well

*(Finally they told that the answer would be \(z^2\), as U1, U2 will be independent, I really don’t remember now how it came that way. And since time was up, they didn’t ask anything else)*

*(Overall I felt it was a bad day for me, there were some gaps in what they were asking and what I was understanding, and I felt interviewing for just 15-20 min is a bit tricky game, it depends on your luck.. If you impress them with the first question they throw at you, half the battle is won.. )*

* Results*: I didn’t had my name in the provisional list, but it was a great experience overall for me.

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