Parameter Estimation for Scientists and Engineers discusses estimating parameters of expectation models of statistical observations. It aims to show scientists and engineers, who often are not aware of estimators other than least squares, that statistical parameter estimation has much more to offer than least squares estimation alone.

The subject of this book is estimating parameters of expectation models of statistical observations. The book describes the most important aspects of the subject for applied scientists and engineers. This group of users is often not aware of estimators other than least squares. Therefore one purpose of this book is to show that statistical parameter estimation has much more to offer than least squares estimation alone. In the approach of this book, knowledge of the distribution of the observations is involved in the choice of estimators. A further advantage of the chosen approach is that it unifies the underlying theory and reduces it to a relatively small collection of coherent, generally applicable principles and notions.