Waveney DIY Centers (WDC) operates a few dozen stores in the eastern United States. The stores are popular with home remodelers, contractors, and do-it-yourself customers. The managers at Waveney are interested in understanding what drives costs as well as getting better cost estimates when planning new stores. The area manager for the Southeast Region is interested in new data analysis approaches to management and offered to run a test using data from the 14 stores in the region.

The initial thoughts of the managers and the financial analysts in the region were that two primary factors drove store costs: store area (square footage) and revenue. The following data were collected from the most recent year of operations (revenues and costs in thousands of dollars).

Store	Revenues ($000)	Area (Square Feet)	Costs ($000)
SE-01	$ 20,745	69,347	$ 15,999
SE-02	15,682	51,617	12,695
SE-03	25,921	83,531	19,410
SE-04	19,589	67,574	15,279
SE-05	19,866	58,709	15,312
SE-06	17,956	67,574	14,299
SE-07	24,705	95,948	18,891
SE-08	12,901	46,298	10,947
SE-09	23,281	78,212	17,653
SE-10	16,030	62,255	13,064
SE-11	20,558	65,801	15,833
SE-12	17,320	72,893	13,997
SE-13	13,874	62,255	11,770
SE-14	23,104	74,666	17,494

Results from a regression of store costs on revenues are as follows.

Equation:
Store costs = $2,691.22 (in thousands) + (66.6% Revenue)
Statistical data
Correlation coefficient	0.999
R2	0.998

Required:

The managers in the region are interested in opening a new store with expected revenues of $20.0 million. Assuming the data and cost estimates from the current stores are appropriate for the new store (SE-17), what are the estimated store costs for store SE-17 using the results from this regression?