Abstract:
Neural networks are seldom used as a modelling tool by statisticians. This is often due to the lack of knowledge in the eld of neural networks as neural networks are frequently perceived as mysterious methods that evolved from the eld of computer science. In this dissertation an attempt will be made to show that neural network methods are closely related to statistical methods. In particular we will show how a backpropagation neural network can be used for statistical applications like regression and classi cation which will include the setting up a of neural network for di erent objectives and also using a neural network for predictive inference. Through simulations we will show an e cient method to t a neural network in practical applications. A neural network will then be employed in a practical application to illustrate how to use a neural network in a regression or classi cation context. This application will also show the necessity of statistical knowledge when using a neural network as a modelling tool.
