Welcome to the session on ‘Continuous Probability Distributions’. In the last session, you learnt about binomial distribution, uniform distribution and cumulative probability.
In this session
You will learn about cumulative probability in detail. You will see how the probability of a continuous variable is expressed and how it is different from the way the probability of a discrete variable is expressed. You will then learn about normal distribution, which is a commonly used probability distribution among continuous random variables.
Prerequisites
There are no prerequisites for this session, other than, of course, knowledge of what was discussed in the previous two sessions.
Guidelines for in-module questions
The in-video and in-content questions for this module are not graded. Note that graded questions are given on a separate page labelled ‘Graded Questions’ at the end of this session. These questions will adhere to the following guidelines:
| First Attempt Marks | Second Attempt Marks | |
| Questions with 2 Attempts | 10 | 5 |
| Questions with 1 Attempt | 10 | 0 |
People you will hear from in this session
Subject Matter Expert
Tricha Anjali
Associate Professor, IIIT- B
The International Institute of Information Technology, Bangalore, also known as IIIT-B, is one of India’s foremost graduate schools. Through its Integrated M.Tech., M.Tech., M.S. (Research) and PhD programs in the IT space, it focuses equally on innovation and education.
Reference Ebook
Statistical Inference for Data Science by Brian Caffo.