This is a business forecasting text that is appropriate for courses in business schools. It focuses on the methods that professional forecasters have found useful and provides a practical tool for students and practitioners. The examples used apply to the Windows version of SORITEC, a commercial software forecasting package. Real-world perspective is given by sidebars written by practitioners and emphasis is placed on the visual inspection of data.
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Introduction to Business Forecasting
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95 percent actual values ARIMA bivariate regression Box-Jenkins Business Forecasting calculated Chapter coefﬁcient Coefficient Std Err combined forecast command line conﬁdence correlogram cycle factor data series data set deseasonalized dialog box disposable personal income domestic car sales dummy variables Durbin-Watson statistic ECONDATA estimates evaluation example exponential smoothing Figure ﬁle ﬁnd ﬁrst forecast horizon forecast values forecasting methods forecasting model four quarters Gap sales gapsales graph Historic before 95 historic period Holdout independent variables Index Journal of Business lags linear mean menu mortgage rate moving average moving-average multiple-regression model normal distribution observations partial autocorrelation pattem private housing starts quarters of 1996 R-squared regression analysis regression model regression results retail sales RMSE root-mean-squared error RSSA sales data sample Schwarz Criterion seasonal indices seasonally adjusted serial correlation shown simple exponential smoothing smoothing constant SORITEC speciﬁc standard deviation Table time-series decomposition time-series plot trend Winters zero