Two different methods of forecasting monthly electrical consumption were compared and the results published in Applied Mathematics and Computation (Vol. 186, 2007). The two methods were Artificial Neural Networks (ANN) and Time Series Regression (TSR). Forecasts were made using each method for each of 4 months. These forecasts were also compared to the actual monthly consumption values. A layout of the design is shown in the accompanying table. The researchers want to compare the mean electrical consumption values of the ANN forecast, TSR forecast, and Actual consumption.

a. Indentify the experimental design employed in the study.
b. A partial ANOVA table for the study is provided on the next page. Fill in the missing entries.

c. Use the information in the table to conduct the appropriate ANOVA F-test using α = .05. State your conclusion in the words of the problem.

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ANN TSR Actual MonthForecast Forecast Consumption Sample Mean 13.480 13.260 13.475 df SS MS F-Value P-Value 08 Source .195 2.83 Forecast Method Month Error Total <0 一10.780 414 069 33.144