Deviation-0.mp3
Deviation-0.mp4
Deviation-I.mp3
Deviation-I.mp4
Deviation-intro.mp3
[Intro]
Is your (Deviation)
Standard
(Man slandered)
Civilization
[Verse 1]
You call this civilized
Hopin’ you’d realized
We create deviate
In all we relate
[Bridge]
Time we pull through
We (me and you)
[Chorus]
Is our (Deviation)
Standard
(Man slandered)
Civilization
(Deviation)
[Bridge]
Devolution
Sour (solution)
[Verse 2]
You call this civilized
More dazed than surprised
We let our deviate
At an exponential rate
[Bridge]
Time we pull through
We (me and you)
[Chorus]
Is our (Deviation)
Standard
(Man slandered)
Civilization
(Deviation)
[Outro]
Devolution
Our sour (solution)
Our are
ABOUT THE SCIENCE
A standard deviation is a statistical measure that quantifies the amount of variation or dispersion in a set of values. In simple terms:
It’s often used in economics and finance to measure risk, volatility, or abnormality in data like stock prices, inflation, or GDP growth.
Real-World Meaning of “Multiple Standard Deviations”
If a metric is “2 standard deviations above the mean,” it means it is significantly higher than usual — so much so that it happens only about 2.5% of the time in a normal distribution.
Current Examples (as of 2024-2025) of Economic/Financial Metrics Showing Multiple Standard Deviations
These examples reflect extreme, unusual, or risky conditions — either positive or negative.
1. Inflation Volatility (U.S.)
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Core inflation variability has been 2–3 standard deviations higher than historical norms at times since 2021.
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Caused by COVID shocks, war, supply chain issues, and erratic monetary policy.
2. Federal Deficit (as % of GDP)
3. Home Prices vs. Median Income
4. Stock Market Valuation (e.g., CAPE Ratio)
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The Shiller CAPE ratio (cyclically adjusted PE) for the S&P 500 is well above long-term averages — often cited as 2–3 standard deviations above its historical mean.
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Signals potential overvaluation or irrational exuberance.
5. Corporate Debt Levels
6. Climate-related Economic Losses
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Insured losses due to climate disasters (floods, fires, hurricanes) have become multiple standard deviations above the 1980s–2000s averages.
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Insurance companies and reinsurers now treat some events as no longer “tail risk” but regular occurrences.