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https://github.com/cyprianfusi/data-scientist-technical-exercise-10ds

With recommendations to UK Department for Education of 10 Local Authorities where National Tutoring Programme (NTP) should be intensified and a response to UK Secretary of Health regarding a 76% Accident and Emergency (A&E) performance target which seems far-fetched.
https://github.com/cyprianfusi/data-scientist-technical-exercise-10ds

data-analysis data-cleaning data-visualization hypothesis-testing pandas-python policy statistics

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With recommendations to UK Department for Education of 10 Local Authorities where National Tutoring Programme (NTP) should be intensified and a response to UK Secretary of Health regarding a 76% Accident and Emergency (A&E) performance target which seems far-fetched.

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# Data-Scientist-Technical-Exercise-10DS

National Tutoring Programme - NTP and Accident and Emergency (A\&E) Performance



This repo contains the work I did as part of a job interview. 

Two days to the interview I was sent a sample exercise from previous interviews with the following statement **"We have attached an example of a technical questions from former interview rounds so that you know what to expect. The policy question and data will both be different for your interview, but hopefully this will give you a good idea of what the task will look like."** This was about the **National Tutoring Programme (NTP)**. An attached word document contained the policy question to be addressed and links to the dataset and other supporting information. I took a whole day to analyse the data and prepared a presentation, just in case I was to be surprised with the same policy question on the interview day. 

This was not the case though, I got a new task on the interview day which was different in approach from the NTP exercise. The new exercise was about **Accident and Emergency (A\&E) Performance**. The exercise were schedule to last´for 4 hours, which involved **analysing the data, answering the policy question and preparing a powerpoint presentation**. 

Four hours were enough time to do the exercise. **But I got lost** after cleaning the data. While reading the problem description I figured out that I was going to carry out a **statistical hypothesis test for one population**. But this information escaped my mind after I had finished preparing the data, making it ready for analysis! I spent more than an hour doing what I would termed **useless analysis**, hoping that I'll find something valuable! **Then my time was up when I had not finished** and when I had not prepared any presentation!

**Needless to say I did not get the job!!**



My advice to future candidates - **Never sit for 4 long hours on an analysis without taking a break!!!** Don't think taking a break would cost you your time! That would by *penny wise, pound foolish*! I have learnt that sleeping over a difficult problem would bring inspiration and in the next day the problem won't appear to be difficult as it previously seemed. I had woken up in the night just to try a new approach to a problem! Getting away from your screen for a few minutes would refresh your brains!! I know it's easily said than done, especially when one is under time presure to deliver!

Anyway, few hors after my time was up I continued working on the exercise and I believe I got back on track! I sent my results to the panel but it was certainly too late!