In: Statistics and Probability
We will often hear that a candidate’s lead is “outside the margin of error” at a 95% confidence level. What does this mean? Why is it dangerous to make predictions “within the margin of error”?
1) Margin of Error indicates the range of values the data lies within above and below the sample statistic when we define a confidence interval. It shows the uncertainty associated with using a sample statistic for predicting a population parameter.
If a candidate's lead is within the margin of error, say 5%, with a 95% confidence interval, it means the lead lies within 5% margin of the real population value 95% of the times.
So, if the lead is "outside the margin of error" at a 95% confidence level, we cannot claim that the lead is within this margin 95% of the times.
2) It is dangerous to make predictions within the margin of error, because statistics aren't guaranteed to be right. These confidence intervals and margin of error are ultimately calculated based on samples, which sometimes can be biased or even inadequate to represent the population as a whole. This can often lead to very misguiding assumptions about the population/ forecasts about future,