100,000 records detail sleep patterns, lifestyle factors, and cognitive performance scores across 12 different occupations. The dataset supports regression and classification tasks for public health analysis.
Use Cases
- Predict cognitive performance scores from sleep and lifestyle variables using regression models.
- Classify individuals into occupation categories based on their sleep health and lifestyle patterns.
- Analyze correlations between specific lifestyle factors and sleep metrics across the 12 occupations.
- Build a model to identify risk factors for poor daily performance from the combined sleep and lifestyle data.
Strengths
- Contains 100,000 records, providing a substantial sample for analysis.
- Covers 12 distinct occupational groups, enabling cross-occupation comparisons.
- Integrates multiple data domains: sleep, lifestyle, and cognitive performance.
Limitations
- Column names and specific features are not provided, limiting precise analytical planning.
- Geographic origin and data collection methodology are unknown, which may affect generalizability.
- Sample data and file formats are unavailable, preventing assessment of data structure prior to download.
Provenance
- Source
- Kaggle
- Collection Method
- null
- Time Range
- null
- Freshness
- null
- Geography
- null