Jackknife method

The Jackknife method is a way to assess the reliability of an estimate, like an average or a measurement, by systematically removing one data point at a time from your dataset and recalculating the estimate. This process shows how much each individual data point influences the overall result. By analyzing these variations, statisticians can gauge the variability, bias, and stability of their estimate, helping them understand its accuracy and confidence level. It's a useful technique to improve the robustness of data analysis without requiring additional data collection.