Hi @MN_8536,
In order to make forecast on a time series, you need to first decide what model you want to use to obtain the forecast. Depending on which model you want to use, you can use different tasks in SAS Studio to obtain the forecast. For example, under Econometrics task-->Univariate Time Series Analysis, you can run ARIMA, ARIMAX, unobserved components model, or regression with autocorrelated errors to obtain the forecast. Under Forecasting task-->Modeling and Forecasting, you can obtain forecast based on ARIMA models, exponential smoothing models, or unobserved components models. For any of these models, you need to select the dependent variable name, which is the variable you want to obtain forecast for. In you case, you have 6 series(for 6 locations),if you want to consider each series individually and perhaps using different types of models using different tasks for different series(locations), then you can select the dependent variable name accordingly each time you work on a series. If you want to use the same type of models hence the same task for all 6 series at the same time, then you may want to restructure your data set such that the 6 series(locations) are stacked over one another with one variable name, say, 'sales', and with a location index variable that indicates which location the observation is taken, then in your task tab, select the 'sales' variable as dependent variable, and select the location index variable as the 'Group Analysis by' variable under 'Additional Roles' . This will perform the analysis separately for each series(location) but you do not need to select each series as dependent variable manually each time.
If you are not familiar with the task interfaces, you may also find it helpful to first experiment with a sample data set in sashelp library, e.g., sashelp.air, and experiment with simple models and obtain forecasts.
I hope this helps. If you have further questions using these tasks, please let me know.
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