Challenge #44: Inspire Europe '16 Grand Prix (L3)

[Computernerd]

My Workflow

[daiphuongngo]

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[daiphuongngo]

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[lwolfie]

Great practice with the predictive tools.

[Tgigs]

My solution attached. Couldnt get an accurate time because I got side tracked. Maybe wouldve been around 15 min.

Lowest p value was the casualty sex = male. So between male and female appears that male increases the likely hood of a fatality.

I feel the model could be more optimized, but was just trying to finish it as quickly as possible. For example, the model took my casualty age variable and one hot encoded it into a bunch of different features. Most or all of which had very high p values. So the age variable should likely be discretized for the model but for the sake of time I did not go through this step.

[olga_strubbe]

A nice challenge, thank you, @GeneR! I did not have the Regression Model as part of my Alteryx tool palette, but I was able to follow the logic for Q 4 & 5 from the model provided.   My solution attached.  

[afnfyz]

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[Rob-Silk]

My solution and answers below:

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Answers:
1)  1.817008
2)  Evening, 4663
3)  Pedestrian, 2562
4)  Pedestrian (P = 0.00011, Est. = 1.86759)
5)  Male (P = 0.00968, Est. = 0.91196)

[IgnacioVilaplana]

Hi all, find my solution attached

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[BS_THE_ANALYST]

Fun challenge. I ran a multi-classification problem into the logistic regression tool. Took me a couple of minutes to realise I needed to produce a dummy variable. Not sure how I feel about create a correlated variable and building a model.