The Epanechnikov kernel is a popular type of probability density function used in statistics, particularly in non-parametric estimation. It is defined by a quadratic function that is zero outside a certain range, making it efficient for smoothing data. The kernel is named after the Russian mathematician Vladimir Epanechnikov, who introduced it in the 1960s. In practical applications, the Epanechnikov kernel is often used in techniques like kernel density estimation, where it helps create smooth curves from discrete data points. Its shape allows for effective estimation while minimizing the bias and variance in the results, making it a valuable tool in data analysis.