Includes bibliographical references (p. 301-302) and index.

Contents: Introduction: The application of statistics to the measurement of damages for lost profits -- Case study 1 - uses of standard deviation -- Case study 2 - Trends and seasonality analysis -- Case study 3 - an introduction to regression analysis and its application to the measurement of economic damages -- Case study 4 - choosing a sales forecasting model: a trial and error process -- Case study 5 - Time series analysis with seasonal -- Case study 6 - cross-sectional regression combined with seasonal indexes to determine lost profits -- Case study 7 - measuring differences in pre- and postincident sale using two sample t- Test versus regression models -- Case study 8 - interrupted time series analysis, holdback forecasting, and variable transformation -- Case study 9 - an exercise in cost estimation to determine saved expenses -- Case study 10 - saved expenses, bivariate model inadequacy, and multiple regression models -- Case study 11 - analysis of and modification to opposing experts' reports -- Case study 12 - further considerations in the determination of lost profits -- Case study 13 - a simple approach to forecasting sales month length adjustment -- Case study 14 - data analysis tools for forecasting sales -- Case study 15 - determination lost sales with stationary -- Case study 16 - determination lost sales using nonregression trend models --