Welcome to the third installment of my 20-project challenge for data analysts and data scientists! This time, we dive into a dataset that sheds light on the operational dynamics of a hospital emergency room (ER). Packed with 9,216 entries and 12 diverse columns, this dataset offers you a chance to explore key metrics like patient demographics, admission trends, wait times, satisfaction scores, and much more.
What’s in the Dataset?
Here’s what you’ll get to analyze:
• Patient Demographics: Including gender, age, and race.
• ER Operations: Wait times, admission flags, and department referrals.
• Satisfaction Metrics: Ratings from patients reflecting their experience.
This dataset is rich with possibilities for exploratory analysis, hypothesis testing, and visualization.
Why Should You Take on This Challenge?
This project will enhance your ability to:
1. Spot Trends: Examine patterns in wait times and satisfaction scores.
2. Correlate Factors: Discover relationships between demographics, department referrals, and admission rates.
3. Sharpen Your Tools: Practice with Excel, Python, SQL, or any tool of your choice.
4. Boost Communication: Present actionable insights through clear visualizations and summaries.
How to Get Started
1. Download the Dataset: Click here to request a copy.
2. Load the data into your preferred analysis tool.
3. Ask and answer questions like:
• How do wait times vary by department and age group?
• Are patients with higher wait times less likely to report satisfaction?
• Which demographic is most frequently referred to specific departments?
Let’s Collaborate!
Once you’ve completed your analysis, share your results with the community! Submit your findings, visualizations, and methodologies to my email at info@oaorogun.co.uk.
I’m interested in this and I would be more than happy to join
Could you forward the data link to ogunleyea452@gmail.com. Thank you