A confidence interval is the mean of your estimate plus and minus the variation in that estimate. This is the range of values you expect your estimate to fall between if you redo your test, within a certain level of confidence.
Confidence, in statistics, is another way to describe probability. For example, if you construct a confidence interval with a 95% confidence level, you are confident that 95 out of 100 times the estimate will fall between the upper and lower values specified by the confidence interval.
Pyth Network uses Confidence Intervals for their Oracle. Publishers submit their best price and range where they believe that price lies. For example, BTC $40,000 +/- $5. For assets that trade on various venues with different participants, information, deposit/withdrawal limits, liquidity profiles, etc. there is no such thing as a “true” price. Using confidence intervals over a single price can reflect a more realistic state of the market and current liquidity conditions, particularly in times of high volatility.
