2 points QUESTION 22 The following ACF plot shows the sample autocorrelations, r, up to lag 10, for the residunts of an ARIMA model fit. The heights of the gray bars are the values of the autocorrelations, and these values are shown on top of the bars. For example, , -0.0057, 0.017, etc. The "lag - autocorrelation is always 1, so we ignore It. Residual Correlogram 1 05 0.216 0.201 rk 0.066 005: 0.005 0.017 1 O O 1 7 16 2 8 9 -0022 -0.080 0.020 -0.023 05 - 1 Leg Use the residual ACF plot above, and the fact that the sample site was n - 89. to compute the Ljung-Box test statistic for testing for white noise up to lag 4. Take your calculations and the final answer to three (3) decimal places. Hint: You do not need Real Statistics or Excel to compute Qgiven the information in the problem. -80989.353 Click Save and Submit to save and subunit. Click Save All Ares to save all answers See All 2 points QUESTION 22 The following ACF plot shows the sample autocorrelations, r, up to lag 10, for the residunts of an ARIMA model fit. The heights of the gray bars are the values of the autocorrelations, and these values are shown on top of the bars. For example, , -0.0057, 0.017, etc. The "lag - autocorrelation is always 1, so we ignore It. Residual Correlogram 1 05 0.216 0.201 rk 0.066 005: 0.005 0.017 1 O O 1 7 16 2 8 9 -0022 -0.080 0.020 -0.023 05 - 1 Leg Use the residual ACF plot above, and the fact that the sample site was n - 89. to compute the Ljung-Box test statistic for testing for white noise up to lag 4. Take your calculations and the final answer to three (3) decimal places. Hint: You do not need Real Statistics or Excel to compute Qgiven the information in the problem. -80989.353 Click Save and Submit to save and subunit. Click Save All Ares to save all answers See All