Question

The following are sales revenues for a large utility company for years 1 through 11. Forecast revenue for years 12 through 15. Because we are forecasting four years into the future, you will need to use linear regression as your forecasting method.

year Revenue (millions)
1 $4,869.0
2 5,072.0
3 5,509.9
4 5,729.6
5 5,498.0
6 5,188.0
7 $5,093.2
8 5,113.6
9 5,558.7
10 5,730.0
11 5,862.3

Answer 1

Using linear regression to forecast sales revenue involves creating a model based on historical data to predict future performance. An electronics retailer's model, ý = 101.32 + 2.48x, allows the prediction of sales growth up to 90 days.

Step-by-step explanation:

For sales revenue prediction using linear regression, we utilize historical data to find a relationship between the passage of time (years) and revenue, which we can then apply to future years.

Using a simple linear regression equation, such as ý = a + bx, where 'x' represents the year and 'ý' represents the predicted sales revenue, we can calculate the expected revenues for future years.

In the example provided related to an electronics retailer, the model ý = 101.32 + 2.48x predicts sales growth where 'x' is the day within 90 days.

For day 60, the prediction would be ý = 101.32 + 2.48(60), and for day 90, it would be ý = 101.32 + 2.48(90).