  For high dimensional data, some of the standard statistical techniques do not
work well. So modification or further development of statistical methods are
necessary. In this paper, we explore these modifications. We start with the
important problem of estimating high dimensional covariance matrix. Then we
explore some of the important statistical techniques such as high dimensional
regression, principal component analysis, multiple testing problems and
classification. We describe some of the fast algorithms that can be readily
applied in practice.
