An R&D department is using multiple regression analysis to forecast its demand for engineering hours. They have identified three key variables they believe influence the demand: the number of ongoing projects, the R&D budget, and the local economic growth rate (see the table below). It is expected that the values of other variables will be the same as in January next year. Month January March February 1447 April May June Actual Engineering Hours July 1572 1517 1592 1723 1651 1595 August 1759 Number of Ongoing Projects 6 9 8 2 2 6 4 3 R&D Budget (in $1000s) 237 190 208 225 214 239 241 219 Local Economic Growth Rate (%) 3.4 1.1 4.8 2.8 2.4 1.7 4.0 2.6

An R&D department is using multiple regression analysis to forecast its demand for engineering hours. They have identified three key variables they believe influence the demand: the number of ongoing projects, the R\&D budget, and the local economic growth rate (see the table below). It is expected that the values of other variables will be the same as in January next year. Based on this regression model, what is the forecasted demand for engineering hours in January next year? 1767 1723 1655 1614