THE TITANIC!!!

We all know the story. At least the love story the movie fed us. Not all is fiction though. There might not have been a Jack or a Rose but there was a ship that sunk in 1912.

This is a project from Gitgirl School of Data, In this session, we learned about the titanic data set.

Joining Gitgirl the first data set I worked on was the titanic data set. It’s apparently common for all newbies to the field.

This is a tutorial on how I obtained my gender based model for the test data set. The objective of the assignment was to estimate who did and who did not survive on the bases of sex.

Observing the train data set and analyzing it using a pivot table to obtain the number of each gender that survived and the ratio to the total number of each gender and the total number of individuals that survived, I was able to establish that 75 % of all females survived the accident. I also surmised that 70% of all survivors were female.

With this my hypothesis was formed. If an individual survived, the person was most likely female. Using that hypothesis i was able to fill out my survived column in the test data set obtaining my gender based model. Now this is not wholly accurate as it only examines one correlating variable(gender). Though given it is a gender based model it serves it’s purpose.

If you are unsure of how to use a pivot table, click the link at the end of this tutorial to learn more.

Any questions should be left in the comments below and I will do well to answer them.

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