Multiple regression models use dummy variables to adjust for seasonal variations in an additive TIME SERIES model.

Question

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Dummy variables are often used in multiple regression models to account for seasonal variations in time series data. These variables help to capture any patterns or fluctuations that occur at specific times of the year (e.g. holiday seasons, shopping periods) that may impact the outcome variable being studied. By including these variables in the regression model, researchers can get a more accurate estimate of the relationship between the predictor variables and the outcome variable while controlling for seasonal effects.

Multiple Regression Models Use Dummy Variables to Adjust for Seasonal