What indicates the appropriate time to use multiple linear regression for forecasting demand?

Using multiple linear regression for forecasting demand is most appropriate when a single variable is insufficient to provide a reliable prediction of future demand. This statistical method allows for the analysis of multiple independent variables to determine their collective impact on a dependent variable, which, in this case, is demand.

In scenarios where demand is influenced by various factors—such as price, promotional activities, economic conditions, and consumer demographics—relying solely on a single variable might lead to an inaccurate or overly simplistic forecast. Multiple linear regression accounts for the complex interrelationships between several factors, providing a more nuanced and accurate model of demand.

To summarize, the correct choice highlights the need for a comprehensive approach in scenarios where various influences are at play in predicting demand, thus validating the use of multiple linear regression.