A Wishart matrix is a type of random matrix that arises in statistics, particularly in multivariate analysis. It is defined as the product of a matrix with its transpose, scaled by a positive definite matrix. The Wishart distribution describes the distribution of such matrices, which is useful for estimating covariance matrices from sample data. Wishart matrices are commonly used in various fields, including finance, machine learning, and signal processing. They help in understanding the properties of sample covariance matrices, which are essential for tasks like hypothesis testing and constructing confidence regions in multivariate statistics.