Part 1 Foundations of forecasting: planning and forecasting; statistical fundamentals for forecasting, appendices: 2-A expected values, 2-B Q-statistic for white noise ACK (k)s.; introduction to regression analysis, supplement 3 - cross correlation function. Part 2 Univariate methods: simple smoothing methods; decomposition and census II methods; trend-seasonal smoothing, supplement 6 - Fourier series analysis. Part 3 Univariate ARIMA methods: ARIMA introduction; ARIMA application; ARIMA forecast profiles. Part 4 Multivariate/causal methods: multiple regression of time series: econometric methods; multivariate ARIMA - transfer functions; multivariate ARIMA - intervention functions. Part 5 Cyclical qualitative, and artificial intelligence methods: cyclical forecasting methods; qualitative and technological forecasting; expert systems, neural networks, and genetic algorithms. Part 6 Combining validation, and managerial issues; combining control and validation methods; method characteristics, accuracy, and data sources.
