#### Sessions on Statistics and Probability Distribution Organized by IIT Bombay

** IIT Bombay **organized a session on

*on*

**“Statistics and Probability Distributions”***and*

**24th February, 26th February***attended by students from Computer Science Engineering Department,*

**02nd March 2016**

**Dronacharya College of Engineering, Gurgaon.**The sessions were delivered by * Prof. Sanjeev Sabnis* from

*discussing in details about*

**IIT Bombay**

**Probability Distribution.***In the First session** Dr. Sabnis *shared his views on Sample Spaces and Event, Axioms of Probability and Permutations and Combinations. Permutations means each of several possible ways in which a set or number of things can be ordered or arranged , on the other hand s combinations is a way of selecting items from a collection such that (unlike permutations) the order of selection does not matter. He explained about law of Total Probability, Bayes Theorem, Dependence & Independence of events, Properties of CDF and PDF.

*is***PDF**

*(PDF - is the derivative of the cumulative density function (CDF). PDF is a function of a random variable, x, and its magnitude will be some indication of the relative likelihood of measuring a particular value. The practical examples given by*

**probability density function***helped students to understand the subject matter and cleared the doubt through Question - Answer session.*

**Dr. Sabnis***In the** Second session, Dr. Sabnis *explained all the key aspects of

*for continuous variable.*

**Probability Distributions***is a table or an equation that links each outcome of a statistical experiment with its*

**Probability distribution***of occurrence. He also discussed in details about Cumulative distribution Function, Variance, Continuous Uniform Distribution, Normal Distribution and Non Standard Normal Distribution. Cumulative distribution Function is a function whose value is the probability that a corresponding continuous random variable has a value less than or equal to the argument of the function.*

**probability**** In the Third session **the professor deeply focused on Binomial Distribution, the Gamma Function, the Weibull Distribution, the Chi Squared Distribution, Students t distribution and F distribution. The

*distribution*

**binomial***specifies the number of times (x) that an event occurs in an independent trials where p is the probability of the event occurring in a single trial. It is an exact probability distribution for any number of discrete trials.*

**function**The whole session provided students good understanding of the subject matter as the students came to know about various concepts of Probability Theory and Distributions.

**All Events**