Moving Average Forecasting Using Sales Data
What is moving average forecasting and how is it used in sales data analysis?
Moving average forecasting is a technique used to analyze trends in data by calculating the average of a certain number of periods. In sales data analysis, it helps in predicting future sales trends based on historical data.
Explanation:
By using a three-month moving average, the forecast sales for periods 4 and 6 are approximately 383 and 448. This is calculated by adding the sales for a given period and the two preceding periods, and then dividing by three.
Understanding Moving Average Forecasting:
Moving average forecasting is a commonly used method to analyze time series data, such as sales data, to identify patterns and make predictions. In this technique, the average of a specific number of recent data points is calculated to smooth out fluctuations and highlight trends.
For sales data analysis, a three-month moving average involves taking the average of sales data from the current period and the two previous periods. This helps in creating a more accurate forecast by incorporating recent trends in sales performance.
In the given scenario, the forecast sales for period 4 are calculated by adding the sales for periods 1, 2, and 3 and dividing by three to get 382.67. Similarly, the forecast sales for period 6 are obtained by adding the sales for periods 3, 4, and 5 and dividing by three to get 448.33.
Therefore, the closest sales forecasts based on the three-month moving average technique are 383 and 448, as mentioned in option b. This method allows businesses to make informed decisions and plan for future sales strategies based on historical data analysis.