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 as follows:

| Period | Fertilizer Sales (tons) | Mowers Sold (six-week lag) | Period | Fertilizer Sales (tons) | 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 |

a. Determine the correlation between the two variables. Does it appear that a relationship exists between these variables that will yield good predictions? (Do not round intermediate calculations and round your answer to 3 decimal places.)

\[ r = \] ___, it appears that a (select one) negative/positive relationship exists between these variables.

b. Obtain a linear regression line for the data. (Negative values should be indicated by a minus sign. Do not round intermediate calculations and round your answers to 3 decimal places.)

\[ Y = \] ___ + ___ \( X_i \)

c. Predict the expected lawn mower sales for the first week in August, given fertilizer sales six weeks earlier of 2 tons. (Round your answer to the nearest whole number.)

Expect ___ mowers to be sold in the first week of August.