DS 412 FALL 06 VER A

DS 412 FALL 06 VER A - a. (id-09” (a (10% 5 b. F3» l/...

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Unformatted text preview: a. (id-09” (a (10% 5 b. F3» l/ 2005\ A \d‘r‘a _ (24 points) Chell Oil Company owns a lease that entitles it to explore for oil on a parcel of offshore land othhe California coast. Since the lease is about to expire, Chell mustdecide whether to drill now for oil at the site, or to sell the lease to Shevron, which has offered $2 million. Chell estimates it would cost $3 million to drill at the site. Ifthe well were dry (probability 0.5), all this cost would be lost. 011 the other hand, ifthe well turned out to be'a minor success (probability 0.3), Chell would earn a net profit of $6 million (after subtracting the drilling cost). Ifthc well turned out to be a major success (probability 0.2), Chell would earn a net profit of$lZ million (after subtracting the drilling cost). Draw the decision tree and label it completebgl showingali nodes, states of nature, decision alternatives, probabilities, andpayoifsi" What should Chell Oil Company decide to do? Why? \ BS 412 ‘ Operations Management Fa112006 Midterm Exam 1 — Part I Prof Uday ligtg: 1. This is the take-home part of the exam. 2. Use MS Excel to answer the question. 3. Your computer printouts must be turned in along with your in—class exam. 4. Please bring this question sheet to your in-class exam. _ ' Sales and Advertising figures for Tritronics, Inc. over a ten year period are shown below. ' Yir Sales ($ millions) Advertising (5 thousands) ‘ 1996 168 242 1997 174 250 . 1998 186 254 , 1999 203 263 2000 205 270 2001 218 275 2002 229 ‘ 285 2003 g 235 . 295 2004 244 298 2005 248 305 a. Run a time series regression with Sales as the dependent variable and Year as the independent variable. b. Run a causal regression with Sales as the dependent variable and Advertising as the independent variable. D8 412 ~ Prof. Uday Yeat Sales Advt. l 168‘ 242 ‘l b 2 174 250 3 186 254 1: 4 203 263 5 205 270 6 218 275 7 229 285 8 235 295 - 9 244 298 ‘ 10 248 305 PART a Ll l 0 2 *5} SUMMARY OUTPUT Regression Statistics - Multiple R 0.993 R Square 0.985 Adjusted R 0.984 Standard E 3.661 Observatio 10 ANOVA df 88 MS F i nificance F Regressior 1 7242.78 7242.78 540.38 1.25E-08 Residual 8 107.22 13.40 ,2 Total 9 7350 M Coefficientsfandard Em t Stat P-value Lower 95%U er 95%.ower 95.09! er 95. 0% Intercept 159.47 2.50 63.76 0.00 153.70 165.23 153.70 165.23 X Variable 9.37 0.40 23.25 0.00 8.44 10.30 8.44 10.30 H PART I) SUMMARY OUTPUT Regression Statistics Multiple R 0.990 R Square 0.980 Adjusted R 0.978 Standard E 4.280 Observatio 10 ANOVA df 88 MS F i nificance F Regressior 1 7203.46 7203.46 393.26 4.36E-08 Residual 8 146.54 18.32 Total 9 7350 m Coefiicients'andard Em t Stat P-vaiue Lower 95%U er 95%.ower 95.09! or 95.0% Intercept 445.91 18.05 -8.08 0.00 -1 87.53 -104.29 -187.53 -1 04.29 X Variable 1.30 0.07 19.83 0.00 1.15 1.46 1.15 1.46 M no ~- advé'ftis Mr L81} 32w (24 points) Monthly sales of DVD players at Good Gals, Inc. has a level pattern, as shown below: Month Jan Feb Mar Apr May Jun Sales 284 276 29] 302 287 280 Use Moving Averages with N = 3 to forecast sales for Apr through Jun. Use 2 de mais. w"? . roman saw For AM» = my” MM) Q h. Assuming a Feb farecast of 276, use Simple Exponential Smoothing with a = 0.1 to forecast sales for 43*, Mar through Jun. Use2 decimals. 9 3 Ff-l 'l' 5 .Ot A {7 + (I ‘VOfb may fwawfifimj .. 0-I x Wei—r (1.50:0 an, m 1% == ‘ H W w W. , 04x WHO—.0»!th “Hanoi W 30> ‘16}?! o'lxer'D+ C l-orl) wan? :. Lam/tiff : DI’IX 731C} ;( l—o-l) = 'LQofb‘G Based on your forecasts for the months of Apr through Jun, compute the MSE for Moving Averages and for Simple Exponential Smoothing. Which method has performed better, and why? .. bf +I5-0X0’5 +I50xo'3 = ENS?) = ha§3z9.:%f../é§._?§9'ff/éé‘”??? / 4:1. EV (.62). = 14.05 .o -2 + (w 0-5” 17/80.:5-32-514if? 3. 74m ” i i '* Emmi??? %.?§?§T+d>¥”‘§[4 " ’ ‘ gun . i- 730 5 50%;.) ZzooZ2 $00 = 0 . 92". .. (9%???“ 6 57‘42‘4a.:2397. “if Z3599 F077: F £998~o+é7éq+lz7gt $.3ZQ #:5130061 ‘——., f? 4035/??? =,. "3 6.; Q¢:%.-?.E7é9 Mi; 943:? ’_77.°_[%_°P° =. 0 ‘5‘? 5 Qrs- .4t.:z§§j_° 1-13“ 7 .___.________———__ D3 4.12—09 ' 3- (W’Q_ Mm em. Fm. a _. ___________ _-.__._ .._.-._._m__-. "WWW-" ._«-..---_. 5.3M -7"91%fl:$_«€._../3_.:_J;i;§2{s- l “Ségé +0199] i -.-_Q’P3i,‘_.":.(?.:_.‘;’ +9; S‘D../}_?£é_)_QLr_EQ:E-fi I ‘ / _____~ '11- CL— w-—-;‘3r?.3» 7 .__..——-A. '-""" [3°C (flsx (acclaim 0-0-0) .- ‘2.-."--.13“!€774?-.7’:(7.-3:7*lflfiéfififliW _. , ol- -..- Ivs-thiv:3.gsr _a_a_<2-:¢°279._- 0.9 ,. = fl Ti}. 359.21%;QELELEEE1? aiiéLééE i 26*?! _..E .Ciilfi 0 14 >- 9 73/23 ...-__£2_;__. ..E_Cfi_aa).._3;¢_4_CEQifl::QE£EQfl?iz<i—Zé151:3 1" 4 = 276 ._ “E. (Ifl-fiiiififlfiifikfifl‘fi:fli§ifliflifiyj 2775 .--f..€fl£*:1):.:°§fi€fl?9 tQ:.E<)_ECAfl;)_19153532313131?2'7 ?~ 95' _.f-.?f_;&.§fi‘bfl)w.7&Q-°90 E9121) = 0 -/ x 187 +0- 7 *3t7j7:_?€§280-64 ._.__2_2:§;ézm-./§:r_3_.3___ __2;z_7-s' -___.»_z+-"‘5"'" 3.87 237.67 42-67" -2794: 7-05 3M 230 273-33 4333 2&0.“ -o-éé ..._.. , .. .-—__ _. ...._.V_..- —— ..._ - —————~——-———-—--p _.. ._.-y......... _.._=__MA = M8E:_Ei§§§?§?€3516:!543913 '3 = I75'éé“ __.._.__..__..__‘__.._.. .. -u- _._... _ ...
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This note was uploaded on 09/09/2011 for the course DS 412 taught by Professor Eng during the Spring '07 term at S.F. State.

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DS 412 FALL 06 VER A - a. (id-09” (a (10% 5 b. F3» l/...

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