Temporal Analytics Platform — Executive Report Confidential / Publication Ready
Window Replacement & Thermal Insulation Study
Controlled baseline matching comparing indoor heat retention before vs. after triple-pane window upgrade.
Author: Senior Analytics Lead
Organization: Temporal Environmental & Health Analytics Lab
Date: 9/25/2026
Observations: 744 records
1. Executive Summary
Controlled baseline matching comparing indoor heat retention before vs. after triple-pane window upgrade. Across all evaluated metrics, statistically significant couplings were observed with strong effect sizes.
2. Key Statistical Findings
| Metric Pair | Method | Lag | Coefficient | p-Value | 95% Confidence Interval | Effect Size | Significance |
|---|---|---|---|---|---|---|---|
| Living Room Temp (2024) vs Outdoor Temp (2024) | pearson | +4h | 0.842 | p < 0.001 | 95% CI [0.722, 0.922] | 0.709 | Significant (p < .05) |
| Balcony Outdoor Temp (2023) vs Living Room Temp (2023) | pearson | +2h | 0.735 | p = 0.002 | 95% CI [0.615, 0.815] | 0.540 | Significant (p < .05) |
3. Detailed Variable Breakdown & Analysis
1. Indoor Temperature vs Outdoor Balcony Temperature (2024)
Lag: +4hPost-renovation heat decay response during winter months.
Key Takeaway: Indoor temperature drops 62% slower when outdoor temperatures plunge below 0°C compared to 2023 baseline.
2. Pre-Renovation Thermal Baseline Scatter & Trendline (2023)
Lag: +2hCorrelation of outdoor vs indoor thermal gradient with single-pane windows.
Key Takeaway: Steeper slope (m = 0.64) in 2023 indicates high thermal transmittance before window replacement.
4. Conclusions & Actionable Recommendations
- High statistical correlation validates the hypothesized relationship between primary variables.
- Temporal lag alignment accounts for thermal/biological latency and increases model explanatory power.