Cost estimation. Hankuk Electronics started production on a sophisticated new smartphone running the Android operating system in January 2020. Given the razor-thin margins in the consumer electronics industry, Hankuks success depends heavily on being able to produce the phone as economically as possible.

At the end of the first year of production, Hankuks controller, Inbee Kim, gathered data on its monthly levels of output, as well as monthly consumption of direct labor-hours (DLH). Inbee views labor-hours as the key driver of Hankuks direct and overhead costs. The information collected by Inbee is provided below:

Month	Output (Units)	Direct Labor-Hours
January	684	1,400
February	492	820
March	660	875
April	504	670
May	612	760
June	636	765
July	648	735
August	600	660
September	648	695
October	696	710
November	672	690
December	675	700

Inbee is keen to examine the relationship between direct labor consumption and output levels. She decides to estimate this relationship using a simple linear regression based on the monthly data. Verify that the following is the result obtained by Inbee:

Regression 1: Direct labor-hours=a+(bOutput units)

Variable	Coefficient	Standard Error	t-Value
Constant	345.24	589.07	0.59
Independent variable: Output units	0.71	0.93	0.76
r2=0.054; Durbin-Watson statistic=0.50

Plot the data and regression line for the above estimation. Evaluate the regression using the criteria of economic plausibility, goodness of fit, and slope of the regression line.

Inbee estimates that Hankuk has a variable cost of $17.50 per direct labor-hour. She expects that Hankuk will produce 650 units in the next month, January 2021. What should she budget as the expected variable cost? How confident is she of her estimate?