multipLe and hybrid independent variables in overhead model Ralph is studying an overhead eost eategory that indudes a variety of produetion support aetivities: minor supplies, minor maintenanee, material handiing,

technieal supervision, and so on. Ralph feels the eosts aggregated in this eategory vary with direet material dollars (DM$), eomplexity of the produets (scored with a eomplexity index and added to give an index ealled eomplexity units) and direet labor hours (DU!). Ralph eolleets the following data from the last 15 months.

The accountant assures Ralph the aecmaIs have been properly done, so there is no issue of hours being reeorded on a lagged basis or anything of that nature.
a] Are the data eonsistent with Ralph's eonjeeture?
b] Suppose Ralph's eonjeeture has merit, but eollinearity stands in the way of statistieal identifieation. Ralph deeides to use the relationship between overhead eost and direet material dollars for library purposes. Is the regression estimate of the slope in this LLA an unbiased estimator of the eorreet slope?AppendixLO1

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t cost DM$ complexity DLH 123456 3,775,238 2,629,042 33,411 188,111 2 3,968,754 2,781,816 49,381 204,240 3 3,685,869 2,570,599 36,844 184,435 3,733,128 2,771,243 34,235 200,086 5 4,101,229 2,833,266 44,215 205,445 3,858,395 2,740,097 33,694 200,229 7 3,887,992 2,710,630 42,619 193,254 8 3,803,625 2,687,639 35,489 196,453 9 4,067,572 2,864,410 39,095 210,573 10 3,990,740 2,713,780 34,498 197,222 11 3,844,263 2,735,144 38,005 198,575 12 3,573,820 2,560,468 37,398 186,031 13 3,820,491 2,664,075 35,734 192,437 14 3,944,296 2,746,627 40,617 199,606 15 3,775,659 2,700,240 35,705 196,983