Final answer:
The model that assumes equal influence of past time periods on future sales is the Moving average. It uses the average of previous sales over a set period as the forecast for the next period, treating historical data points with equal weight. Option D is correct.
Step-by-step explanation:
The forecasting model that assumes previous time periods have an equal influence on future sales is D. Moving average. A moving average forecasting model calculates the average of sales over a specific number of previous time periods and uses this average as the forecast for the next period. This model assigns the same weight to all the historical data points it considers, assuming that each historical period is equally relevant to predicting the future.
For the economist working on predicting outcomes on the stock market, or the electronics retailer looking to forecast sales growth, applying the moving average method can help smooth out short-term fluctuations and highlight longer-term trends in the data. It is important to note, however, that a moving average model would not account for any potential trends or seasonality in the sales data.
The forecasting model that assumes previous time periods have an equal influence on future sales is D. Moving average.
A moving average is a statistical technique used to analyze data points by creating a series of averages of different subsets of the full data set. In this model, each previous time period is given equal weight, meaning that the influence of older data diminishes as new data becomes available.
For example, if a moving average is calculated using the past 3 time periods, each period carries equal weight in the calculation, and the average is updated as each new period is added.