Welcome to Week 3 of the ThotWave Healthcare Analytics Challenge. We are delighted to see so many people challenging themselves and dedicating a few minutes each week to improving their analytics and leadership capabilities.
Last week, we provided a summary of the week 1 challenge and asked you to consider the general steps that you use when starting the process of analyzing data.
This week, we will make things less ethereal and far more real for you by pointing you to a dataset and then asking you to use your sleuthing skills to find some interesting phenomenon in the data. In case you don’t want to fend for yourself, we have provided some useful “guide-rails” for your data exploration.
Finding Your Story
Turning data into a story is hard. People understand that stories are powerful, but don’t have the scaffolding they need to turn their data into one. This challenge introduces the concept of the “data story” by having you think of the different types of stories that we share. Your favorite movie genre might be Action-Adventure while others may enjoy documentaries or comedies. Similarly, when we think of data, we should consider different “story types” that can be found in data.
Starting to understand a dataset can be daunting. One approach to helping you is to begin to think about the various stories we might be able to tell about the data. There are five types of stories that we can use to guide this process:
- Interaction stories
- Comparison stories
- Change stories
- Personal stories
- Factual stories
For this week’s challenge, we will guide you through an analysis of education data provided by the Programme for International Student Assessment (PISA), which is run by the Organisation for Economic
Co-operation and Development (OECD).
PISA conducts a study in which they test more than half a million 15-year-olds in three subjects—maths, reading and science. The goal of the study is to provide a three-year snapshot of how educational systems compare across countries. We have included links below to the latest results which were published on December 6, 2016 for this week’s challenge. In the December 10th issue of the Economist, they highlighted some of the results (which were not all that favorable for the United States), so your task is to find out whether interesting interactions might yield deeper insights.
Note PISA provides a number of individual datasets that you can use for exploration, but we will limit our focus on the “School questionnaire” data. For your analysis, you have two choices:
- Use SAS or SPSS to construct your analysis dataset (Click here to download a database of your choice)
- Use the PISA interactive tools to begin your query (Click here begin your online analysis)
So how should you begin? To guide you on your way, we will use an interaction story to help guide your analysis.
Click Start Challenge below to begin the Healthcare Analytics Challenge: Week 3.
Are you ready to formally dive into data visualization and take your skillset and capabilities to the next level? Register for our Healthcare Data Visualization Best Practices workshop today!