The two numbers are related. If a survey has an estimated error of ±5% at 95% confidence, it also has an estimated error of ±6.6% at 99% confidence. ±x% at 95% confidence is always ±1.32x% at 99% confidence.
According to statistics, there's about a 50:50 chance that this survey was (in)correct.
The smaller the estimated error, the larger the required sample, at a given confidence level.
at 95.4% confidence:
±1% would require 10,000 people. ±2% would require 2,500 people. ±3% would require 1,111 people. ±4% would require 625 people. ±5% would require 400 people. ±10% would require 100 people. ±20% would require 25 people. ±25% would require 16 people. ±50% would require 4 people.
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