AI Analysis: Consolidated Energy Statistics

Executive Summary

Canada's Consolidated Energy Statistics dataset (Statistics Canada, Table 25100079) covers 72 months of monthly energy data from January 2020 to December 2025, tracking 12 fuel types and 11 supply/demand characteristics across 6,858 valid records measured in Terajoules. The data is highly right-skewed — with values ranging from -262,853 TJ to 2,198,725 TJ and a mean (156,700 TJ) far exceeding the median (15,311 TJ) — reflecting the outsized dominance of a few high-volume fuel categories such as Primary Energy, Crude Oil, and Natural Gas. Outlier analysis flagged 479 records (7.0%) as statistically extreme, while 650 negative values were identified as legitimate accounting entries representing exports, stock drawdowns, and statistical adjustments.

Key Findings

• The dataset contains 6,858 valid records spanning 72 monthly periods from January 2020 to December 2025, with values measured in Terajoules across 12 fuel types and 11 supply/demand characteristics.
• Total Primary Energy has the highest mean value (476,046 TJ) and widest range (2,461,578 TJ) of any fuel type, making it the most dominant and variable category in Canada's energy mix.
• Crude Oil and Natural Gas follow as the next largest categories, with means of 288,765 TJ and 222,600 TJ respectively, and correspondingly large standard deviations indicating significant month-to-month variability.
• The distribution is heavily right-skewed, with a mean of 156,700 TJ versus a median of just 15,311 TJ, and an IQR spanning 724 to 158,652 TJ — confirming that a small number of very large values drive the overall average.
• 479 records (7.0%) were flagged as statistical outliers using a 3× IQR method, with bounds set at -473,058 to 632,434 TJ, against an overall data range of -262,853 to 2,198,725 TJ.
• 650 negative values are present in the dataset, concentrated in Stock Variation (291 records), Other Adjustments (213 records), and Inter-product Transfers (144 records), reflecting legitimate energy accounting entries rather than data errors.
• Correlation analysis across 8 supply and demand variables for Total Primary & Secondary Energy reveals that production and supply metrics tend to cluster with strong positive correlations near +1.0, while some variables show near-zero or negative relationships, indicating independent or inverse energy flows.