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Example 3-1(1)
Course: ECON 101, Spring 2012School: Pomona College
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'11 Month January February March April May June July August September October November December January Actual Jan 2011 Abs Error 4MA Jan 2011 Abs Error 6MA Demand 89 57 144 221 177 280 223 286 212 275 188 312 260 13.25 10.66667 Jan 2011 Forecast 4MA 246.75 6MA 249.3333 Feb 2011 Forecast 4MA 258.75 Using Excel Month Demand 4MA 6MA Error 4MA Error RMA January 89 February 57 #N/A #N/A March 144 #N/A #N/A April...
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Coursehero >> California >> Pomona College >> ECON 101Course Hero has millions of student submitted documents similar to the one
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below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
'11 Month
January
February
March
April
May
June
July
August
September
October
November
December
January Actual
Jan 2011 Abs Error 4MA
Jan 2011 Abs Error 6MA
Demand
89
57
144
221
177
280
223
286
212
275
188
312
260
13.25
10.66667
Jan 2011 Forecast
4MA
246.75
6MA
249.3333
Feb 2011 Forecast
4MA
258.75
Using Excel
Month
Demand
4MA
6MA
Error 4MA Error RMA
January
89
February
57
#N/A
#N/A
March
144
#N/A
#N/A
April
221
#N/A
#N/A
May
177
127.75
#N/A
June
280
149.75
#N/A
July
223
205.5 61.666666667
August
286
225.25 161.3333
17.5 183.6667
60.75 102.33333333
September
212
241.5 221.8333
-29.5 -9.8333333333
October
275
250.25 233.1667
24.75 41.833333333
November
188
249 242.1667
-61 -54.16666667
December
312
240.25
244
71.75
68
January
260
246.75 249.3333
13.25 10.666666667
258.75
255.5
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Pomona College - ECON - 101
MonthJanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecemberDemand Weighted Demand895714422117728022328621227568.7518856.4312140.4Jan 2011 Forecast3WMA6WMA22.328.631.85537.678265.55253.3
Pomona College - ECON - 101
MonthJanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecemberComparison WorksheetJan 2011 fcst 4MAJan 2011 fcst 6MAJan 2011 fcst 3WMAJan 2011 fcst 6WMAJan 2011 fcst SESJan 2011 ActualsDemand Forecast8957144221177
Pomona College - ECON - 101
PeriodDemand Avg Sales Seasonality Avg Sea. Factor for like periodDeseasonalized DemandPeriod2011 Avg Forecast2009 Q125002607.50.960.982563.11 2011 Q1Q221502607.50.820.802675.47 Q2Q330002607.51.151.162586.44 Q3Q427802607.51.071.
Pomona College - ECON - 101
GenerationalDiversity:MasteringtheBoomerXYDivideKarenBedellSuccession planning the development of successors for top leadership and management roles iscritical for any company. The smooth transition of power and leadership, of management and institutio
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How to Win at Office Politicsby Kelly Pate DwyerLike it or not, every workplace is a political environment. But operating effectivelywithin it doesnt have to mean sucking up, lying, or slinging dirt. In its purest form, officepolitics is simply about
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For the exclusive use of V. PATELHarvard Business SchoolManagement Education Alliance9-898-238Rev. January 26, 2000Pioneer Hi-Bred International, Inc.Supply ManagementIn early February 1997, the preliminary 1998 production and distribution schedule
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10014-01_Ch01.qxd8/18/06110:28 AMPage 13Four Irresistible Forcesfor Increased Labor MobilityFour irresistible forces today cause observed increases inlabor mobilityand each promises to become even morepowerful in the future. These forces are wag
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My family medical doctors in my last 8 or nine years of periodic visit hardly spent 2 full minutestalking to me. When I needed to visit emergency ward in hospital, Doctor came to talk to meonly for 5 minute or less, and charged 650 USD that was a networ
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Lecture 3: Digital VideoEn-hui YangUniversity of WaterlooEn-hui YangECE 415: Multimedia CommunicationsRepresentation of Digital VideoDigital video is represented by a sequence of moving digitalimages shown in quick succession. Each moving image is
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Lecture 4: The Notion of Lossless CodesEn-hui YangUniversity of WaterlooEn-hui YangECE 415: Multimedia CommunicationsGeneral Lossless CodesNotationX : a source alphabet with its cardinality 2; in typical textcompression, X = cfw_0, 1, , 255.X n (
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Lecture 5: EntropyEn-hui YangUniversity of WaterlooEn-hui YangECE 415: Multimedia CommunicationsEntropyLet X be a random variable taking values in X with probabilitymass function (pmf) p(x ) = Prcfw_X = x , x X , whereX = cfw_a0 , a1 , , aJ 1 .De
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Lecture 6: Connecting Entropy to UniquelyDecodable CodesEn-hui YangUniversity of WaterlooEn-hui YangECE 415: Multimedia CommunicationsKraft InequalityC (X1 )C (X2 ) X = X1 X2 Memorylesscoder CDMSRate RKraft inequalityEntropy H (X )Figure: 6.
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Lecture 7: Huffman CodingEn-hui YangUniversity of WaterlooEn-hui YangECE 415: Multimedia CommunicationsGiven a pmf pj = p(aj ), 0 j J 1, overX = cfw_a0 , a1 , , aJ 1 we now look at how to design an optimal prex code C such thatJ 1R=pj |C (aj )|
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Lecture 8: Arithmetic CodingBasic IdeaEn-hui YangUniversity of WaterlooEn-hui YangECE 415: Multimedia CommunicationsDrawbacks of Huffman CodingIn principle, the Huffman coding algorithm can also be appliedto design optimal prex codes with block len
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Lecture 9: Adaptive Arithmetic CodingEn-hui YangUniversity of WaterlooEn-hui YangECE 415: Multimedia CommunicationsUniversal Source CodingIn Huffman coding and arithmetic coding discussed so far, boththe encoder and decoder are assumed to know the
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Lecture 10: Run Length CodingEn-hui YangUniversity of WaterlooEn-hui YangECE 415: Multimedia CommunicationsBasic IdeaRun length coding is efcient for data sequences where longsegments of repeated symbols (runs) appear. Consider, forexample, a bina
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Lecture 11: Lempel-Ziv CodingEn-hui YangUniversity of WaterlooEn-hui YangECE 415: Multimedia CommunicationsLempel-Ziv codes are universal codes which are based onstring matching. Since the original work of Ziv and Lempel inlater 1970s, many variant
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ECE 415: Multimedia CommunicationsHomework Set 11Due Monday, Jan. 23, 2012 (Hand in to your TA)The following problems are from Section 5 (Exercises) of Chapter 3 of Reference Book [1]:1. Problem 22. Problem 43. Problem 54. Problem 65. Problem 8
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