29 Feb 2024

Posted on:

08 Feb 2024

0

# Resolved:Better interpretation of Step 3 required

I have not understood the importance and purpose of Step 3. I need a better interpretation of Step3: Log Likelihood. I seek a few answers which might resolve my query: What is the essence of carrying out this step? What does the value obtained in this step mean? How do we interprete this value? I would like to understand the interpretation of this step in simpler terms - information on source of formula would be an added benefit.

Instructor
Posted on:

29 Feb 2024

0

Hello again, Dhaivat!

I understand your curiosity about the Log Likelihood step in logistic regression and its importance. I will try to break it down to make it clearer.

What is Log Likelihood?

In the realm of statistics, especially when dealing with logistic regression, Log Likelihood is a pivotal concept. It's a statistical measure that tells us how well our model fits the data. Think of it as evaluating how good a key fits into a lock; the better it fits, the more likely it is the right key.

Why Do We Calculate It?

The calculation of Log Likelihood serves a very important purpose. It helps us in identifying the best set of parameters (coefficients) for our logistic model that makes the observed data most probable.

How Do We Interpret This Value?

By maximizing this value through various techniques, we ensure that our model is as accurate as possible in predicting outcomes.

Source of the Formula

The formula for Log Likelihood in logistic regression is derived from principles of probability and statistical theory, particularly from the concept of likelihood in the context of the Bernoulli distribution, which is suitable for binary outcomes. This mathematical foundation comes from the work of statisticians who developed these models to describe binary data effectively.

Hope this helps!

Best,

The 365 Team