Estimator of Variance

This lecture covers the concept of estimators, focusing on the variance estimator. The instructor introduces the idea of creating a personal estimator for the mean, exploring the process of inventing estimators for mu based on data density. The lecture emphasizes the importance of unbiased estimators and corrects the bias in the sample variance estimator. Additionally, it discusses the Mean Square Error (MSE) of an estimator and provides practical exercises to compute bias. The content includes detailed explanations and examples of variance estimation techniques, highlighting the significance of accurate estimations in statistical analysis.