Confidence Intervals

Confidence intervals (CIs) are a powerful and elegant way to quantify uncertainty in estimates. Instead of providing a single-point estimate—such as an average sales increase of 5% next year—a confidence interval gives a range, say [3%, 7%], within which the true value is likely to lie. In an ideal world, we could make highly precise estimates with full confidence, but in reality, these are often competing trade-offs.

What makes confidence intervals particularly valuable for businesses is their flexibility: they allow you to balance precision and confidence based on your specific needs. In some cases—such as pricing strategy optimization or forecasting demand—you may prioritize precision, even if it means accepting some risk. In other cases—like financial risk assessments—you may prefer a more conservative approach, accepting a slightly broader range to minimize uncertainty.

The lecture below was recorded for tutorial groups of the course Research Methods and Statistics, a while ago. Here I cover:

• The nuts and bolts of confidence intervals
• How to balance precision with confidence
• How to avoid misinterpreting confidence intervals