Titanic – Who do you think survived? Data Modeling by an Actuarial Student

letsanalyze titanic dataset (1)

Do you think you could have predicted who will survive the crash before it actually happened? With the saddest story of a century, people are using the data to predict and analyze various things like what led to survival or death. Sometimes, data helps understand the reasons, simply because numbers provide information. Here is an attempt to get a deeper insight into what happened in a dreadful shipwreck.

The study by Vaibhav Agarwal FRM, an actuarial professional with 12 papers cleared, covers intuitive factors that might have lead to survival, such as a passenger’s gender, age, or socioeconomic status. Numerous variables serve as close proxies to this information about the passenger, such as ticket price paid, or the class of boarding.

He analyzes the probabilities based on the outcomes recorded for the list of passengers, and derived conclusions as to what might have caused these outcomes.

Earlier, we discussed with him the possibilities of Actuarial analytics and Risk Consulting, you can read the interview here.

The language used in the paper is extremely simple and Titanic makes it interesting enough to read about it and for anyone looking to get introduced to analytics. In an attempt to #predict who #survived the Titanic crash, it’s an absolutely wonderful analysis of the Titanic data.

Vaibhav has worked in diverse domains of risk consulting and analytics. He moved ahead to start his journey on interesting datasets on www.letsanalyze.in

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