Computational Modelling in Psychology introduces the principles of using computational models in psychology and provides a clear idea about how model construction, parameter estimation and model selection are carried out in practice. The book is written at a level that permits readers with a background in cognition, but without any modeling expertise. The authors present the content step-by-step by moving from the basic concepts of modeling to issues and application. The book is structured to make clear the logic of individual component techniques and how they relate to each other. The authors focus on the logic of models and the types of arguments that can be made from them, as well as providing detailed practical knowledge about parameter-estimation techniques and model selection and so on. Readability is emphasized throughout to make the necessary mathematics and programming less daunting for beginners. The book's supporting web page provides additional information and programming code.

Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. Financial Modeling bridges this gap between theory and practice by providing a nuts-and-bolts guide to solving common financial models with spreadsheets. Simon Benninga takes the reader step by step through each model, showing how it can be solved using Microsoft Excel. The long-awaited third edition of this standard text maintains the "cookbook" features and Excel dependence that have made the first and second editions so popular. It also offers significant new material, with new chapters covering such topics as bank valuation, the Black-Litterman approach to portfolio optimization, Monte Carlo methods and their applications to option pricing, and using array functions and formulas. Other chapters, including those on basic financial calculations, portfolio models, calculating the variance-covariance matrix, and generating random numbers, have been revised, with many offering substantially new and improved material. Other areas covered include financial statement modeling, leasing, standard portfolio problems, value at risk (VaR), real options, duration and immunization, and term structure modeling. Technical chapters treat such topics as data tables, matrices, the Gauss-Seidel method, and tips for using Excel. The last section of the text covers the Visual Basic for Applications (VBA) techniques needed for the book. The accompanying CD contains Excel worksheets and solutions to end-of-chapter exercises.