Chips Bakery has been having trouble forecasting the demand for its special high-fiber bread and would like your assistance. The data for the weekly demand and the autocorrelations of the original data and various differences of the data are shown in Tables P-7A-D.

a. Inspect the autocorrelation plots and suggest a tentative model for these data. How did you decide on this model?
b. Using a computer program for ARIMA modeling, fit and check your identified model with the bread demand data.
c. Write down the equation for forecasting the demand for high-fiber bread for period 53.
d. Using a computer program for ARIMA modeling, forecast the demand for high-fiber bread for the next four periods from forecast origin 52. Also, construct 95% prediction intervals.

TABLE P-7A Weekly Sales Demand for High-Fiber Bread (in 1,000s) Week Demand Wek Demand Week Demand Week Demand 1 22.46 14 30.21 27 39.29 4 2 2027 15 309 28396 4 50.08 3 20.7 16 33,04 2 4102 42 50.25 4 23.68 31 30425243 49.00 5 23.25 18 32.44 3 40.8344 49.97 6 23.48 34.73 32 4215 45 52.52 7 24.8 20 34.92 3343.9146 3.39 8 25-442 33.3 3445.67 5237 924.88 22 3691 44534 54.06 10 2738 23 3775 36 45.23 4 5488 11 27.74 24 35.46 37 4635 50 54,82 12 28.96 25 34838 4628 1 56.23 13 28.4826 37.39 46.70 52 57.54 TABLE P:7B Sample Autocorrelations for Original Data Lag Autocorrelation Lag Autocorrelation 59 53 48 43 .38 32 12 TABLE P-7C Autocorrelations for the First-Differenced Series Lag Autocorrelation Lag Autocorrelation 40 29 17 21 -03 -03 -05 TABLE P-7D Autocorrelations for the Second-Differenced Series Lag Autocorrelation Lag Autocorrelation -53 -10 16 10 .20 16 13 12