Christine is analysing the errors of a HES model. The data analysed is quarterly sales of...

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Christine is analysing the errors of a HES model. The data analysed is quarterly sales of a given company. Supplied below are the time series and autocorrelation plots of the in- sample errors of the model. What would be a correct conclusion for Christine to make from these plots? Autocorrelation Autocorrelatio 04 02 " 42 04 4 4 10 Lag a. There is evidence to suggest the errors have a positive trend component, and a hence a model that can incorporate trend would be a better fit for this data. O b. There is not enough evidence to say the errors are not random, and hence the model is a reasonable predictor of the data in this case. c. There is enough evidence to say the errors are random, and hence the model is a reasonable predictor of the data in this case. d. There is evidence to suggest the errors have a seasonal component, and a hence a model that can incorporate seasonal variations would be a better fit for this data. Christine is analysing the errors of a HES model. The data analysed is quarterly sales of a given company. Supplied below are the time series and autocorrelation plots of the in- sample errors of the model. What would be a correct conclusion for Christine to make from these plots? Autocorrelation Autocorrelatio 04 02 " 42 04 4 4 10 Lag a. There is evidence to suggest the errors have a positive trend component, and a hence a model that can incorporate trend would be a better fit for this data. O b. There is not enough evidence to say the errors are not random, and hence the model is a reasonable predictor of the data in this case. c. There is enough evidence to say the errors are random, and hence the model is a reasonable predictor of the data in this case. d. There is evidence to suggest the errors have a seasonal component, and a hence a model that can incorporate seasonal variations would be a better fit for this data.