Focusing on business forecasting, this edition discusses the basic statistical techniques that are useful for preparing individual business forecasts and long-range plans. It features ten plant service tours which aim to give students a close look at internal operations in different companies.
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A REVIEW OF BASIC STATISTICAL CONCEPTS
EXPLORING DATA PATTERNS AND CHOOSING
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ARIMA autocorrelation coefficients Autocorrelation function Box-Jenkins Business Forecasting calculated Chapter chi-square column component correlation coefficient correlogram cyclical data points determine developed dialog box dialog box appears differenced different from zero distribution dollars Durbin-Watson statistic emergency road service error terms estimate Example exponential smoothing following menus fore forecast error forecasting methods forecasting model forecasting process forecasting techniques future gallons increase independent variables indicates linear MAPE mean measured Minitab month monthly sales moving average multiple regression Neural Networks null hypothesis observations output packages parameters partial autocorrelation pattern period plot population predict predictor variables problem procedure quarter regression analysis regression coefficient regression equation regression line regression model relationship residuals scatter diagram seasonal indexes selected serial correlation shown in Figure shown in Table smoothing constant standard deviation standard error StDev STUDY trend estimate variance Window Help