Analysis of data for an autoregressive forecasting model produced the following

Question

Analysis of data for an autoregressive forecasting model produced the following tables. CoefficientsStandard Error t Statistic p-value 3.745787 0.84426 0.34299 0.0828491.66023 0.103822 0.035709 14.650446.69E-19 3.85094 0.70434 0.62669 Intercept t-2 df MS p-value Regression Residual Total 135753.5 67876.76 107.33361.91E-17 27192.79 632.3904 162946.3 43 45 The actual values of this time series, y, were 228, 54, and 191 for May, June, and July, respectively. The forecast value predicted by the model for July is 101.00 104.54 218.71 21.56 -77.81 0 0

Explanation / Answer

Analysis of data for an autoregressive forecasting model produced the following tables. CoefficientsStandard Error t Statistic p-value 3.745787 0.84426 0.34299 0.0828491.66023 0.103822 0.035709 14.650446.69E-19 3.85094 0.70434 0.62669 Intercept t-2 df MS p-value Regression Residual Total 135753.5 67876.76 107.33361.91E-17 27192.79 632.3904 162946.3 43 45 The actual values of this time series, y, were 228, 54, and 191 for May, June, and July, respectively. The forecast value predicted by the model for July is 101.00 104.54 218.71 21.56 -77.81 0 0

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