Answer the question below based on pic I attached.

Evaluate the adequacy of the model. Check on the Box-Pierce statistics. Large p-values indicate random errors, meaning the model is adequate; small p-values indicate pattern, meaning the model is not adequate

ARIMA Model: DESE1 Estimates at Each Iteration Iteration SSE Parameters 0 215182783 0.100 233.473 194404941 -0.050 271.205 2 182609069 -0.200 309.379 3 179646202 -0.316 339.314 4 179638611 -0.322 341.028 179638591 -0.322 341.123 Relative change in each estimate less than 0.001 Final Estimates of Parameters Type Coef SE Coef T-Value P-Value AR 1 -0.3220 0.0913 -3.53 0.001 Constant 341 123 2.77 0.007Ditterencing: 1 regular ditterence Number of observations: Original series 111, after differencing 110 Residual Sums of Squares DF SS MS 108 179633044 1663269 Back forecasts excluded Modified Box-Pierce (Ljung-Box) Chi-Square Statistic Lag 12 24 36 48 Chi-Square 23.76 47.47 64.57 89.22 DF 10 22 34 46 P-Value 0.008 0.001 0.001 0.000