Title: Analysis of data (Diabetis dataset)
Budget: $30 – $250 USD
analyze a dataset
Exploratory data analysis is important for understanding the following healthcare considerations:
Predicting and diagnosing illnesses
Improving patient safety
Reducing time to diagnosis
Increasing our understanding of disease risks and causes
Developing stronger prevention strategies
Data fetching/API integration
Data analysis
Testing
6–8 visualizations of data (at least two per question)
Write-up summarizes major findings and implications at a professional level
Each question in the project proposal is answered with precise descriptions and findings
Findings are strongly supported with numbers and visualizations
Each question response is supported with a well-discerned statistical analysis from lessons (e.g., aggregation, correlation, comparison, summary statistics, sentiment analysis, and time series analysis)
Exploratory data analysis is important for understanding the following healthcare considerations:
Predicting and diagnosing illnesses
Improving patient safety
Reducing time to diagnosis
Increasing our understanding of disease risks and causes
Developing stronger prevention strategies
Data fetching/API integration
Data analysis
Testing
6–8 visualizations of data (at least two per question)
Write-up summarizes major findings and implications at a professional level
Each question in the project proposal is answered with precise descriptions and findings
Findings are strongly supported with numbers and visualizations
Each question response is supported with a well-discerned statistical analysis from lessons (e.g., aggregation, correlation, comparison, summary statistics, sentiment analysis, and time series analysis)