For forecasting expenditure, which method would be most appropriate?

Time series analysis and linear regression are highly effective methods for forecasting expenditure because they utilize historical data to identify trends and patterns over time. Time series analysis examines how variables, such as expenses, behave across different time periods, thereby allowing businesses to make predictions based on past performance. Linear regression builds on this by establishing a relationship between the expenditure and one or more independent variables, facilitating more refined forecasts that account for both trends and correlations.

This method is particularly useful for creating budget estimates, as it can accommodate seasonal variations and long-term economic changes, providing a more accurate forecast than other approaches. In contrast, while basic budgeting principles offer a foundational structure for managing finances, they may not effectively capture the dynamics involved in expenditure forecasting. Sales expert consultations can provide valuable insights, but they are subjective and may not be grounded in historical data. Standard deviation calculations could assist in understanding the variability of expenditures but lack the predictive capabilities necessary for effective forecasting. Thus, time series analysis and linear regression stand out as the most appropriate method for accurate expenditure forecasting.