Probability and Probability Distributions - Overview

Welcome to this session on ‘Probability and Probability Distributions’. In the previous session, you learnt about descriptive statistics, i.e., numbers and figures that can help you in describing and understanding a data set. Inferential statistics, on the other hand, involves picking a sample out of the population data set and then trying to understand the population data set on the basis of that sample.

Naturally, the samples might not be representative of the entire population. Hence, the inference made from any sample might not accurately describe the population. However, it is possible to assign a probability value to the accuracy of any inference made about the population from the sample. This session will focus on establishing the theoretical frameworks necessary to explore such topics in greater detail.

In this Session

You will learn how to approach statistically uncertain events and focus on the following topics:

1. Probability
2. Random Variables
3. Probability Distributions
4. Normal Distribution
5. Standard Normal Distribution and Z-Score

People you will hear from in this session

Thomas Dougherty

Xpert, upGrad 

Thomas has a long association with the field of data science. He has experience of working with data and has taught data science. He is currently an Executive in Residence at a well-known university in Rhode Island, USA. Prior to working as an Executive in Residence, Thomas has led data science teams across many industries, including the travel, telecom, automotive, consulting and investment industries, to name a few.

The transcript of this session is provided below for your reference.

You are now ready to start this session!

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