Background Background The
The Glass Glass Slipper Slipper restaurant restaurant has has operated operated in in a a resort resort community community near near a a popular popular ski ski area area of of New New Mexico Mexico and and busiestbusiest during the rst 3 months of the
during the rst 3 months of the year. The Glass slipper oered the ultimate dining experience with year. The Glass slipper oered the ultimate dining experience with breathtaking !iews of thebreathtaking !iews of the surrounding mountains. "ames and #eena $eltee% the owner% place special attention in setting the
surrounding mountains. "ames and #eena $eltee% the owner% place special attention in setting the perfect ambiance making diningperfect ambiance making dining a truly magnicent gourment experience. The Glass Slipper has de!eloped and maintained a reputation as one of the
a truly magnicent gourment experience. The Glass Slipper has de!eloped and maintained a reputation as one of the &must !isit&&must !isit& places in that region of New Mexico.
places in that region of New Mexico.
Objective Objective
'fter
'fter careful careful analysis analysis of of their their nancial nancial condition% condition% the the $eltee(s $eltee(s decided decided to to sell sell the the Glass Glass Slipper Slipper and and open open a a bed bed andand breakfast on a beautiful beach in Mexico. 'lthough not retired yet% this
breakfast on a beautiful beach in Mexico. 'lthough not retired yet% this would put them in the would put them in the retirement setting they ha!e beenretirement setting they ha!e been longing for many years. They would ha!e to hire a manager that would
longing for many years. They would ha!e to hire a manager that would allow them to begin a semi)retirement life allow them to begin a semi)retirement life in paradise. Thein paradise. The Glass Slipper for the right price. The price
Glass Slipper for the right price. The price of the business would be based on the !alue of the business would be based on the !alue of the property and e*uipment% as well asof the property and e*uipment% as well as pro+ections of future income. ' forecast of sales for the next year is
pro+ections of future income. ' forecast of sales for the next year is needed to help in the needed to help in the determination of the calue of thedetermination of the calue of the restaurant. Monthly sales for each of
restaurant. Monthly sales for each of the past 3 the past 3 years are pro!ided below.years are pro!ided below.
Monthly ,e!enue -in /%000s1 Monthly ,e!enue -in /%000s1
M Moonntthh 222222 2222 222222 "anuary "anuary 3434 2222 55 6 6eebbrruuaarryy //77 2222 3377 M Maarrcchh // 2222 33 ' 'pprriill 33//88 2222 333388 M Maayy 330044 2222 3333// "une "une 9090 2222 9595 "uly "uly 9090 2222 9494 ' 'uugguusstt 99//44 2222 9933// S Seepptteemmbbee 990099 2222 999900 : :ccttoobbeerr 999955 2222 9933 N Noo!!eemmbbee 99;;00 2222 998877 # #eecceemmbbeerr 33//55 2222 333300
12-Month Moving Average
Forecasting Simple Linear egression Num pds /9
!ata Forecasts and "rror Anal#sis
Month !emand Forecast "rror Absolute S$uared Abs %ct "rr "an)08 38 6eb)08 90 Mar)08 / 'pr)08 3/8 May)08 304 "un)08 90 "ul)08 90 'ug)08 9/4 Sep)08 /78 :ct)08 995 No!)08 9;0 #ec)08 3/5 "an)07 300.000 /.000 /.000 90;34.000 0.39 6eb)07 95 300.500 /9.500 /9.500 /5500.950 0.973 Mar)07 93 300.7/; /99.083 /99.083 /70.30 0.987 'pr)07 33/ 30/.44; 97.333 97.333 840. 0.087 May)07 3/8 309.;50 /5.950 /5.950 939.543 0.08 "un)07 95 303.;50 )58.;50 58.;50 35/.543 0.90 "ul)07 955 30./4; )7./4; 7./4; 9/;.34/ 0./73 'ug)07 993 305./; )89./; 89./; 4;79.50; 0.3;0 Sep)07 9/0 304.000 )74.000 74.000 79/4.000 0.5; :ct)07 933 30;.000 );.000 ;.000 5;4.000 0.3/8 No!)07 9;8 30;.44; )97.44; 97.44; 880./// 0./0; #ec)07 399 308.333 /3.44; /3.44; /84.;;8 0.09 "an)/0 50 308.7/; //.083 //.083 /770.50; 0.3/ 6eb)/0 38 307./; /98.583 /98.583 /4533.4; 0.97 Mar)/0 3 3/0.500 /93.500 /93.500 /5959.950 0.985 'pr)/0 338 3//./; 94.583 94.583 ;04.4; 0.0;7 May)/0 33/ 3/9.000 /7.000 /7.000 34/.000 0.05; "un)/0 95 3/3.083 )57.083 57.083 370.80 0.933 0 100 200 300 400 500 Value Enter the past demands in the data area
Enter the past demands in the data area
The lines abo!e the &forecast li the &forecast line& show their o sales as each New <ear begins. issue and the &Gray& is perfor
"ul)/0 94 3/3.833 )7.833 7.833 983.34/ 0./87 'ug)/0 93/ 3/.583 )83.583 83.583 4784./; 0.349 Sep)/0 99 3/5.950 )7/.950 7/.950 8394.543 0.0; :ct)/0 93 3/4./; );3./; ;3./; 5370.00; 0.309 No!)/0 987 3/;.950 )98.950 98.950 ;78.043 0.078 #ec)/0 335 3/8./4; /4.833 /4.833 983.34/ 0.050 Total /97.000 /4;7.833 /4//;0.387 5.3; Average &'()& *+'++( *)1&',(( '22)
Bias MA! MS" MA%" S" .&'&+2
Forecasting
Demand Forecast
Time
ne& illustrate their busiest months% while the lines below season. The graph also shows moderate increase in . =asically% the up and down is more of a seasonality
egression Anal#sis eression Anal#sis Forecasting Simple linear regression
!ata Forecasts and "rror Anal#sis
Month !emand #3 %eriod03 Forecast "rror Absolute S$uared Abs %ct "rr
"an)08 38 / 397.;9; /08.9;3 /08.9;3 //;93./09 0.9; 6eb)08 90 9 398.545 7/.35 7/.35 8340.37 0.9/8 Mar)08 / 3 39;.09 84.578 84.578 ;77./ 0.907 'pr)08 3/8 394.90 )8.90 8.90 4;.709 0.094 May)08 304 5 395.0;8 )/7.0;8 /7.0;8 343.7;3 0.049 "un)08 90 4 393.7/4 )83.7/4 83.7/4 ;0/.88/ 0.350 "ul)08 90 ; 399.;5 )89.;5 89.;5 488./8 0.35 'ug)08 9/4 8 39/.579 )/05.579 /05.579 ///7.58 0.87 Sep)08 /78 7 390.97 )/99.97 /99.97 /788.745 0.4/8 :ct)08 995 /0 3/7.94; )7.94; 7.94; 8884.3/8 0./7 No!)08 9;0 // 3/8./05 )8./05 8./05 93/./0/ 0./;8 #ec)08 3/5 /9 3/4.73 )/.73 /.73 3.;;5 0.004 "an)07 /3 3/5.;8/ /98.9/7 /98.9/7 /40./48 0.987 6eb)07 95 / 3/.4/7 //0.38/ //0.38/ /9/8.07 0.940 Mar)07 93 /5 3/3.54 /07.5 /07.5 //777.;88 0.957 'pr)07 33/ /4 3/9.97 /8.;04 /8.;04 37.703 0.05; May)07 3/8 /; 3//./39 4.848 4.848 ;./48 0.099 "un)07 95 /8 307.7;0 )4.7;0 4.7;0 99/.07; 0.945 "ul)07 955 /7 308.808 )53.808 53.808 9875.980 0.9// 'ug)07 993 90 30;.44 )8.44 8.44 ;/4.885 0.380 Sep)07 9/0 9/ 304.83 )74.83 74.83 7307.043 0.57 :ct)07 933 99 305.39/ );9.39/ ;9.39/ 5930.3; 0.3/0 No!)07 9;8 93 30./57 )94./57 94./57 48.309 0.07 #ec)07 399 9 309.77; /7.003 /7.003 34/.// 0.057 "an)/0 50 95 30/.835 /8./45 /8./45 9/759.7/4 0.397 6eb)/0 38 94 300.4;3 /3;.39; /3;.39; /8858.;75 0.3/ Mar)/0 3 9; 977.5// /3.87 /3.87 /808;.93 0.3/0 'pr)/0 338 98 978.38 37.459 37.459 /5;9.953 0.//; May)/0 33/ 97 97;./84 33.8/ 33.8/ //3.3; 0./09 0 5 10 0 100 200 300 400 500 Col >f this is trend analysis then simply enter the past demands in the demand column. then enter the y%x pairs with y rst and enter a new !alue of x at the bottom in orde >f this is trend analysis then simply enter the past demands in the demand column. > then enter the y%x pairs with y rst and enter a new !alue of x at the b ottom in order
The seasonality is consistent but the slo positi!e performance trend line% the reg raw data is found to be? 4 5 (('..+ - 1'
The Slope of the trend line is negati!e w seasonal index in "an and 6eb causes the negati!e slope.
"un)/0 95 30 974.09 )9.09 9.09 /;44.0/7 0./45 "ul)/0 94 3/ 97.849 )30.849 30.849 759.55 0.//; 'ug)/0 93/ 39 973.;00 )49.;00 49.;00 373/.959 0.9;/ Sep)/0 99 33 979.538 )48.538 48.538 47;.37 0.304 :ct)/0 93 3 97/.3;5 )8.3;5 8.3;5 930./;; 0./77 No!)/0 987 35 970.9/3 )/.9/3 /.9/3 /.;9 0.00 #ec)/0 335 34 987.05/ 5.77 5.77 9///.304 0./3; Total 0.000 934.8; 99;57.373 8.90 7ntercept (('..+ Average ' *)'*+ *(2'.1* '22.
Slope -1'1*2 Bias MA! MS" MA%"
S" .1'..
Forecast 2.)'...+ 3;
8orrelation -'1& 8oe9cient o determination '2(
15 20 25 30 35 40
Regression
mn B Linear (Column B) >f this is causal regression
to forecast y.
f this is causal regression to forecast y.
e is not. $hile the /9)month mo!ing a!erage plotted a ession plotted a negati!e trend line. ' trend line based on the
*26
ich would indicate that sales are declining o!er time. The high trend line on the unad+usted data to appear to ha!e a
Multiplicative !ecomposition
Forecasting !ecomposition: multiplicative
/9 seasons
!ata Foreca
Month !emand #3 ;ime 03 Average atio Seasonal Smoothed <nadjusted Adjusted
"an)08 38 / 307.387 /./4 /.35 305.908 975.730 9.485 6eb)08 90 9 307.387 /.358 /.389 303.83 974.477 /0./95 Mar)08 / 3 307.387 /.338 /.347 309.330 97;.48 0;.33 'pr)08 3/8 307.387 /.098 /.043 977.05 978.93; 3/;.// May)08 304 5 307.387 0.787 /.097 97;.09 977.004 30;.45/ "un)08 90 4 307.387 0.;;4 0.;74 30/.3 977.;;5 938.4;7 "ul)08 90 ; 307.387 0.;;4 0.8/8 973.7/ 300.5 95.;4; 'ug)08 9/4 8 307.387 0.478 0.;99 977.930 30/.3/3 9/;.50 Sep)08 /78 7 307.387 0.40 0.48/ 970.;84 309.083 905.479 :ct)08 995 /0 307.387 0.;9; 0.;55 97;.7/ 309.859 998.;97 No!)08 9;0 // 307.387 0.8;3 0.709 977.07 303.49/ 9;3.;78 #ec)08 3/5 /9 307.387 /.0/8 /.0; 300.;75 30.370 3/8.;45 "an)07 /3 307.387 /.35 /.35 307.387 305./57 3;.730 6eb)07 95 / 307.387 /.3; /.389 30;.40 305.798 99.883 Mar)07 93 /5 307.387 /.34; /.347 308.709 304.47; /7.78/ 'pr)07 33/ /4 307.387 /.0;0 /.043 3//.9;0 30;.44 394.755 May)07 3/8 /; 307.387 /.098 /.097 307.045 308.935 3/;./4 "un)07 95 /8 307.387 0.;79 0.;74 30;.;/ 307.00 94.09; "ul)07 955 /7 307.387 0.89 0.8/8 3//.835 307.;;3 953.3/ 'ug)07 993 90 307.387 0.;9/ 0.;99 308.79; 3/0.53 99./44 Sep)07 9/0 9/ 307.387 0.4;7 0.48/ 308./0 3//.3/9 9//.7;4 :ct)07 933 99 307.387 0.;53 0.;55 308.504 3/9.08/ 935.;00 No!)07 9;8 93 307.387 0.877 0.709 308.980 3/9.850 989./9/ #ec)07 399 9 307.387 /.0/ /.0; 30;.;7 3/3.4/7 398.30 "an)/0 50 95 307.387 /.5 /.35 3/3.5;0 3/.388 5/./;
Enter past demands in the data area. Do not change the time period numbers!
Enter past demands in the data area. Do not change the time period numbers!
6eb)/0 38 94 307.387 /./4 /.389 3/4.84 3/5./5; 35.40 Mar)/0 3 9; 307.387 /.03 /.347 3/4.735 3/5.794 39.4/7 'pr)/0 338 98 307.387 /.079 /.043 3/;.859 3/4.475 334.;47 May)/0 33/ 97 307.387 /.0;0 /.097 39/.;00 3/;.4 394.49 "un)/0 95 30 307.387 0.89/ 0.;74 3/7.0/8 3/8.933 953.3;5 "ul)/0 94 3/ 307.387 0.853 0.8/8 399.8/ 3/7.009 940.84/ 'ug)/0 93/ 39 307.387 0.;; 0.;99 390.0/0 3/7.;;9 930.898 Sep)/0 99 33 307.387 0.;9 0.48/ 398.7;0 390.5/ 9/8.940 :ct)/0 93 3 307.387 0.;85 0.;55 39/.;; 39/.3/0 99.4;0 No!)/0 987 35 307.387 0.73 0.709 390.;8 399.0;7 970.3 #ec)/0 335 34 307.387 /.083 /.0; 3/7.873 399.88 338.075 Total '!erage >ntercept 975./4/ Slope 0.;47
atios
Season / Season 9 Season 3 Season Season 5 Season 4 Season ; Season 8 Season 7
/./4 /.358 /.338 /.098 0.787 0.;;4 0.;;4 0.478 0.40
/.35 /.3; /.34; /.0;0 /.098 0.;79 0.89 0.;9/ 0.4;7
/.5 /./4 /.03 /.079 /.0;0 0.89/ 0.853 0.;; 0.;9
'!erage /.35 /.389 /.347 /.043 /.097 0.;74 0.8/8 0.;99 0.48/
Forecasts
@eriod Anad+usted Seasonal 'd+usted 3; 393.4/; /.35 4./7 38 39.384 /.389 8.37; 37 395./55 /.347 5.954 0 395.79 /.043 34.583 / 394.473 /.097 334./38 9 39;.49 0.;74 940.;93 3 398.939 0.8/8 948.08 397.00/ 0.;99 93;.70 5 397.;;0 0.48/ 99.5 4 330.537 0.;55 97.40 ; 33/.308 0.709 978.;44 8 339.0;; /.0; 3;.;40
6orecasted sales for each month of the next year. The gi!es the seasonal indices% the unad+usted forecasts found using the trend line% and the nal -ad+usted1 forecasts for the next year
1 2 3 4 5 6 7 0 50 100 150 200 250 300 350 400 450 500 Forecasts
sts and "rror Anal#sis
"rror ="rror= "rror>2 Abs %ct "rr
/3.3/5 /3.3/5 /;;.985 0.030 7.8;5 7.8;5 7;.50; 0.09 4.45; 4.45; .390 0.0/4 0.857 0.857 0.;3; 0.003 )/.45/ /.45/ 9.;9 0.005 /.39/ /.39/ /.;5 0.004 )5.;4; 5.;4; 33.94 0.09 )/.50 /.50 9.949 0.00; );.479 ;.479 57./49 0.037 )3.;97 3.;97 /3.708 0.0/; )3.;78 3.;78 /.98 0.0/ )3.;45 3.;45 /./; 0.0/9 4.0;0 4.0;0 34.850 0.0/ 9.//; 9.//; .83 0.005 3.0/7 3.0/7 7.//; 0.00; .05 .05 /4.357 0.0/9 0.85 0.85 0.;97 0.003 )/.09; /.09; /.055 0.00 /.484 /.484 9.8/ 0.00; )/./44 /./44 /.340 0.005 )/.7;4 /.7;4 3.70 0.007 )9.;00 9.;00 ;.988 0.0/9 )./9/ ./9/ /4.789 0.0/5 )4.30 4.30 /.39 0.090 )/./; /./; /.3;8 0.003
9.340 9.340 5.5;0 0.005 /.38/ /.38/ /.708 0.003 /.93/ /.93/ /.5/ 0.00 .358 .358 /8.770 0.0/3 0.495 0.495 0.370 0.009 3./37 3./37 7.85/ 0.0/9 0./;9 0./;9 0.030 0.00/ 5.;0 5.;0 39.7; 0.094 0.330 0.330 0./07 0.00/ )/.3 /.3 9.08 0.005 )3.075 3.075 7.5;; 0.007 /8.// /90./70 488./;5 0.373 0.503 3.337 /7.//4 0.0// =ias M'# MSB M'@B SB 5.573
Season /0 Season // Season /9 0.;9; 0.8;3 /.0/8 0.;53 0.877 /.0/ 0.;85 0.73 /.083 0.;55 0.709 /.0; ! 10 11 12
Forecasting
!ecomposition: multiplicative
/9 seasons!ata
@eriod #emand -y1 Time -x1 '!erage ,atio Seasonal Smoothe Anad+uste
"an)08 38 / /.59 303.9979 975.38; 6eb)08 90 9 /.370597 309.033 974.95/ Mar)08 / 3 /.3;;/9 300.49; 97;./054 'pr)08 3/8 /.0;/70; 974.44;4 97;.744 May)08 304 5 /.03;/59 975.0388 978.8945 "un)08 90 4 0.;7505 30/.;33 977.48; "ul)08 90 ; 300 300.95 0.;7733 0.8/9044 975.595 300.5; 'ug)08 9/4 8 300.5 300.;083 0.;/830 0.;/88;8 300.483 30/.0;7 Sep)08 /78 7 300.7/4; 30/.97/; 0.45;/;/ 0.44495/ 97;./853 309.948 :ct)08 995 /0 30/.444; 309.9083 0.;59 0.;400; 30/.4057 303./988 No!)08 9;0 // 309.;5 303.95 0.87035 0.8877/8 303.3788 303.7873 #ec)08 3/5 /9 303.;5 303.7583 /.034394 /.03/;88 305.9753 30.87; "an)07 /3 30./44; 30.;7/; /.54;33 /.59 30;.383/ 305.;/09 6eb)07 95 / 305./4; 305.;083 /.3709/ /.370597 305.437/ 304.5;0; Mar)07 93 /5 304 304.5 /.380078 /.3;;/9 30;./49; 30;.3// 'pr)07 33/ /4 30; 30;.3333 /.0;;00; /.0;/70; 308.;755 308.97/4 May)07 3/8 /; 30;.444; 308 /.03948 /.03;/59 304.4087 307./59/ "un)07 95 /8 308.3333 308.495 0.;738 0.;7505 308.0/7/ 3/0.0/95 "ul)07 955 /7 308.7/4; 307./44; 0.89;78 0.8/9044 3/.0/37 3/0.8;3 'ug)07 993 90 307./4; 307.7583 0.;/759 0.;/88;8 3/0.905; 3//.;33 Sep)07 9/0 9/ 3/0.5 3/0.7583 0.4;5339 0.44495/ 3/5./745 3/9.5737 :ct)07 933 99 3//./4; 3//.;083 0.;;7 0.;400; 3/9.397; 3/3.5 No!)07 9;8 93 3/9 3/9.5/; 0.8878/ 0.8877/8 3/9.388 3/.3/8 #ec)07 399 9 3/3.0833 3/3.583 /.09;95 /.03/;88 3/9.0;74 3/5./;53 "an)/0 50 95 3/3.8333 3/.9083 /.39/;/ /.59 3//.5347 3/4.0358 6eb)/0 38 94 3/.5833 3/.7/4; /.3708 /.370597 3/.788 3/4.8749 Mar)/0 3 9; 3/5.95 3/5.8333 /.3;/9 /.3;;/9 3/5./50 3/;.;54; 'pr)/0 338 98 3/4./4; 3/4.8333 /.04480; /.0;/70; 3/5.3957 3/8.4/;/ May)/0 33/ 97 3/;.95 3/;.;083 /.0/834 /.03;/59 3/7./33 3/7.;;4 "un)/0 95 30 3/8./44; 3/8.;083 0.;7474; 0.;7505 3/7.33/ 390.338/ "ul)/0 94 3/ 3/7.95 0.8/9044 395.0748 39/./785 'ug)/0 93/ 39 0.;/88;8 39/.339 399.057 Sep)/0 99 33 0.44495/ 334.9074 399.7/75 :ct)/0 93 3 0.;400; 395.;3 393.;;77
Enter past demands in the data area. Do not change the time period numbers!
Enter past demands in the data area. Do not change the time period numbers!
No!)/0 987 35 0.8877/8 39.;7 39.40
#ec)/0 335 34 /.03/;88 39.4;7/ 395.5008
'!erage >ntercept 97.599 Slope 0.84043 atios
Season / Season 9 Season 3 Season Season 5 Season 4 Season ; Season 8 0.;7733 0.;/830 /.54;39; /.3709/ /.380078 /.0;;00; /.03948 0.;738 0.89;78 0.;/759 /.39/;08 /.3708 /.3;/9 /.04480; /.0/834 0.;7474;
'!erage /.5/8 /.370597 /.3;;/9 /.0;/70; /.03;/59 0.;7505 0.8/9044 0.;/88;8 Forecasts
@eriod Anad+usted Seasonal 'd+usted 3; 394.34/3/ /.59 ;/./39 38 39;.99/;; /.370597 55.0// 37 398.0899 /.3;;/9 5/.808; 0 398.79; /.0;/70; 359.5757 / 397.803/4 /.03;/59 39.0557 9 330.44349 0.;7505 943.0//4 3 33/.5907 0.8/9044 947.9/7 339.3855 0.;/88;8 938.737 5 333.950/ 0.44495/ 999.098 4 33./05; 0.;400; 97.97 ; 33.7457 0.8877/8 978.0799 8 335.894 /.03/;88 34.50/;
Forecasts and "rror Anal#sis
'd+usted Brror CBrrorC BrrorD9 'bs @ct Brr 94.4487 //.33// //.33// /98.3737 09.57E //.73;5 8.04958 8.04958 45.0048 0/.79E 07./50/ .87703 .87703 93.59/54 0/./;E 3/7.37/8 )/.37/8/ /.37/8/ /.73;/34 00.E 307.7985 )3.7985 3.79853 /5.39; 0/.98E 938.3;94 /.49;374 /.49;374 9.48/; 00.48E 9.043 ).043/ .043/3 /4.5/84 0/.47E 9/4.4;5 )0.4;5 0.4;538 0.549/4 00.3/E 90/.3844 )3.38449 3.38449 //.479 0/.;/E 994./34/ )/./34/ /./34074 /.970;/5 00.50E 9;0.5955 )0.59559 0.59559/ 0.9;4/;9 00./7E 3/.503 0.57484 0.57484 0.9//3// 00./5E /.583; 9./434 9./434 5.838;94 00.5E 94.975 )/.9753 /.9753 /.4;8/37 00.30E 93.3474 )0.34749 0.34749 0./344/7 00.07E 330.578 0.50/43 0.50/43 0.97/;;4 00./4E 390.43;4 )9.43;49 9.43;4/4 4.75;0/4 00.83E 94.5854 )/.5854 /.58540/ 9.5//39 00.45E 959.73 9.55044 9.55044 4.505844 0/.00E 99.0789 )/.07895 /.07894 /.904/5 00.7E 908.944 /.;337;/ /.;337;/ 3.004455 00.83E 933.837 )0.83709 0.837095 0.;03749 00.34E 9;7.;/ )/.;// /.;//3 9.7379/3 00.49E 395./7/ )3./707 3./7073 /0.90993 00.77E 54.78 )4.78/ 4.78/ 9.99738 0/.E 0.453 )9.453/ 9.4530; ;.005;/ 00.4/E 3;.587/ )3.587/ 3.587/ /9.88/75 00.83E 3/.59;7 )3.59;84 3.59;84 /9.589 0/.0E 33/.348 )0.34;8 0.34;;7 0./90955 00./0E 95.;784 )0.;784 0.;78577 0.43;;4 00.3/E 940.83 3./45433 3./45433 /0.09/93 0/.90E 93/.59// )0.59/05 0.59/055 0.9;/78 00.93E 9/5./5 8.85549 8.85549 ;8.039; 03.75E 9/.59 /.580; /.580; 9./9570/ 00.40E
988.7033 0.07447 0.07447 0.00735 00.03E 335.8;7 )0.8;8; 0.8;8;9 0.;/888; 00.95E Total 0.59/983 73.;;9/ ;4.0;/ 30.//E 0.0/8 9.40;89 /3.99353 00.8E =ias M'# MSB M'@B SB .45/;9/
Season 7 Season /0Season //Season /9 0.45;/;/ 0.;59 0.87035 /.034394 0.4;5339 0.;;7 0.8878/ /.09;95 0.44495/ 0.;400; 0.8877/8 /.03/;88
Forecasting
;rend adjusted e0ponential smoothing
'lpha =eta
!ata Forecasts and "rror Anal#sis
@eriod #emand Brror 'bsolute S*uared
@eriod / 0 0 0 0 0 @eriod 9 0 0 0 0 0 0 @eriod 3 0 0 0 0 0 0 @eriod 0 0 0 0 0 0 @eriod 5 0 0 0 0 0 0 @eriod 4 0 0 0 0 0 0 @eriod ; 0 0 0 0 0 0 @eriod 8 0 0 0 0 0 0 /e0tperiod Total 0 0 0 Average Bias MA! MS" S" Smoothed Forecast, Ft Smoothed Trend, Tt Forecast Including Trend, FITt
Enter alpha and beta (between 0 and 1, enter the past demands in the shaded column then enter a starting orecast. I the starting orecast is not in the irst period then delete the error anal"sis or all rows abo#e the starting orecast.
Enter alpha and beta (between 0 and 1, enter the past demands in the shaded column then enter a starting orecast. I the starting orecast is not in the irst period then delete the error anal"sis or all rows abo#e the starting orecast.
2#>F0H 2#>F0H ?!7@ MA%" 'bs @ct Brr 1 2 3 4 5 6 7 0 0'1 0'2 0'3 0'4 0'5 0'6 0'7 0' 0'! 1 Forecasting
Demand %mooted Forecast Ft Time
I'TB $'JSK 'SS:L>'TBS
Forecasting
"0ponential smoothing
'lpha 0./
!ata Forecasts and "rror Anal#sis
@eriod #emand Forecast "rror Absolute S$uared Abs %ct "rr
@eriod / ;0 45 5 5 95 0;./E @eriod 9 48.5 45.5 3 3 7 0.38E @eriod 3 4.8 45.8 )/ / / 0/.5E @eriod ;/.; 45.; 4 4 34 08.3;E @eriod 5 ;/.3 44.3 5 5 95 0;.0/E @eriod 4 ;9.8 44.8 4 4 34 0.089/;589 Total 9 94 /39 34.47E Average , ,'(((((( 22 *'11C
Bias MA! MS" MA%" S" &'),,&*(
/e0t period *)', #>SLASS>:N
5.97? Asing exponential smoothing forecast for 'ugust(s income is 4;%00. Enter alpha (between 0 and 1, enter the past demands in the shaded column then enter a starting orecast. I the starting orecast is not in the irst period then delete the error anal"sis or all rows abo#e the starting orecast.
Enter alpha (between 0 and 1, enter the past demands in the shaded column then enter a starting orecast. I the starting orecast is not in the irst period then delete the error anal"sis or all rows abo#e the starting orecast.
1 2 3 4 5 60 62 64 66 6 70 72 74 Forecasting 70 65 Time Value
DA;" EALS ASSO87A;"S
Forecasting
"0ponential smoothing
'lpha 0.3
!ata Forecasts and "rror Anal#sis
@eriod #emand Forecast "rror Absolute S$uared Abs %ct "rr
M:NTK/ ;0 45 5 5 95 0;./E M:NTK 9 48.5 44.5 9 9 09.79E M:NTK 3 4.8 4;./ )9.3 9.3 5.97 03.55E M:NTK ;/.; 44./ 5.97 5.97 9;.78/ 0;.38E M:NTK 5 ;/.3 4;.77; 3.303 3.303 /0.7078/ 0.43E M:NTK 4 ;9.8 48.78;7 3.8/9/ 3.8/9/ /.539// 0.059340// Total /;./05/ 9/.;05/ 8;.;/409 30.84E Average 2'.&.& ('*1)&1) 1,'*1+(, &'1,C
Bias MA! MS" MA%" S" ,'*.2.,1
/e0t period )'1(1&( #>SLASS>:N
5.30? Asing alpha of 0./ %M'# !alue is .333 while using alpha of 0.3 %M'# !alue is 3.4/8. =ased on this using alpha of 0.3 pro!ides a better forecast since it has a lower M'# !alue.
1 2 3 4 5 60 62 64 66 6 70 72 74 Forecasting 70 65 Time Value E o a En or ab
ter alpha (between 0 and 1, enter the past demands in the shaded column then enter a starting recast. I the starting orecast is not in the irst period then delete the error anal"sis or all rows
o#e the starting orecast.
ter alpha (between 0 and 1, enter the past demands in the shaded column then enter a starting ecast. I the starting orecast is not in the irst period then delete the error anal"sis or all rows o#e the starting orecast.
