Question

Lovely Lawns, Inc., intends to use sales of lawn fertilizer to predict lawn mower sales. The store manager estimates a probable six-week lag between fertilizer sales and mower sales. The pertinent data are:

Period Fertilizer
Sales
(tons) Number of
Mowers Sold
(six-week lag) Period Fertilizer Sales
(tons) Number of
Mowers Sold
(six-week lag)
1 1.6 10 8 1.3 7
2 1.3 8 9 1.7 10
3 1.8 11 10 1.2 6
4 2.0 12 11 1.9 11
5 2.2 12 12 1.4 8
6 1.6 9 13 1.7 10
7 1.5 8 14 1.6 9

obtain a linear regression line for the above data, and use it to predict expected lawn mower sales. what percent (%) of the variation is in fact explained by the linear regression line? (round your answer to a whole number. show percent value without showing percent sign. for example, if your answer is 36%, simply enter your answer as 36.)

Answer 1

The subject question involves using historical fertilizer sales data to predict future lawn mower sales using a regression model. Detailed analysis with a six-week lag period is suggested for best forecasting results.

Step-by-step explanation:

Lovely Lawns, Inc. is attempting to predict lawn mower sales based on fertilizer sales, with a six-week lag between the two. The numbers provided, although unclear, seem to relate to weekly data on fertilizer sales (e.g., Week 6: 1.6 units of fertilizer sold, followed by an expected Week 13: 1.7 units of lawn mower sales).

To accurately forecast mower sales, the store manager could use statistical methods like a time series analysis that includes a regression model, wherein the independent variable (fertilizer sales) is used to forecast the dependent variable (lawn mower sales) with a specified time lag.

It would be beneficial to organize the data chronologically and analyze it using a regression model that incorporates time lag to optimize inventory and sales strategies.