Political polls are a staple of election season, providing insight into which candidate holds a lead. However, it’s crucial to interpret these polls carefully, especially when it comes to the standard error (SE) — a key statistic that indicates how much the poll results might vary from the true population sentiment.

What is Standard Error?

The standard error represents the margin of error in the poll’s results. It reflects the variability of the sample, and its size is influenced by both the sample size and the degree of variability in responses. A lower SE suggests more confidence that the poll reflects the actual views of the population, while a higher SE implies less certainty.

SE is important because it helps us assess how reliable the polling numbers are. In political polling, the reported “margin of error” (MOE) is typically based on the standard error, with most polls using a 95% confidence interval. This means that if we repeated the poll multiple times, we’d expect the true population result to fall within the margin of error 95% of the time.

Example: Trump vs. Harris General Election Polls

Let’s look at an example from recent Trump vs. Harris general election polls in Georgia.  The poll, conducted by Pollster YouGov and sponsored by CBS News was conducted September 20-24 and showed the following results:

• Trump: 51%
• Harris: 49%
• Sample size (n): 1,441 Likely Voters (LVs)
• Margin of Error (MOE): ±3.5 percentage points

With a 3.5% margin of error, this means Trump’s true support could be as low as 47.5% or as high as 54.5%, and Harris’s support could range between 45.5% and 52.5%.

Why the Standard Error Matters

In this example, the 2-point lead that Trump holds over Harris is within the poll’s margin of error, meaning it’s not statistically significant. The race is essentially a toss-up, as the poll results are too close to draw firm conclusions. This is why understanding the standard error and margin of error is crucial — even when one candidate appears to be ahead, the lead may not be as solid as it seems.

Takeaway

When interpreting political polls, always consider the standard error and the margin of error. A lead within the margin means the race could go either way, and polls should be viewed as a snapshot of current sentiment, not a guarantee of the final outcome.

As the Trump vs. Harris example shows, even small leads should be treated with caution when the standard error is factored in.