Black box analysis with linear regression on global warming

Abstract

This paper demonstrates that the conclusions drawn from datasets on global temperature anomaly and atmospheric CO2 from NOAA can vary depending on the range of investigated periods. By examining the data from both macroscopic and microscopic perspectives, the study reveals that different levels of analysis can produce different outcomes from the same datasets based on statistics.

Keywords

• Linear regression
• Global warming
• CO2 and temperature anomaly
• p-value and R-squared