<p>Slope estimates from linear regression model fits for forecastability (Ω) vs. forecast

Slope estimates from linear regression models analyzing the relationship between forecastability and forecast performance for COVID-19 and influenza hospital admissions. The data, published by Lauren A. White, includes results for ensemble and baseline models at U.S. state and national scales. Values are reported with three significant figures, with statistical significance indicated at a p=0.05 threshold.

Use Cases

• Compare forecastability-performance relationships for COVID-19 versus influenza based on the described regression slopes.
• Assess the statistical significance of forecastability metrics for different models and geographic scales.
• Validate or benchmark ensemble forecasting models against baseline models for hospital admissions.

Strengths

• Statistical significance is explicitly indicated for each result at a p=0.05 threshold.
• Values are reported with three significant figures, suggesting a controlled level of precision.
• Data is licensed under CC-BY-4.0, permitting open reuse with attribution.

Limitations

• The dataset is very small at 9.5 KB, indicating limited scope and likely a summary of results rather than raw data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Derived from linear regression model fits for forecastability vs. performance, as shown in a referenced scientific figure.

Freshness

Last updated 2026-04-15 17:57:23; freshness should be verified.

Geography

U.S. state and national scales