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8/3/2019 62707413 Ulker Chocolate Bars Assignment
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Graduate School of Business
M K T G 9 0 1 G r o u p 1 0
MKTG 901
ÜLKER CHOCOLATE BARS ASSIGNMENT
28.12.2010
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G du t School of Busin ss
M K T G 9 0 1 1
ÜL
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1) To find the breakeven point, the cost of consumer promotion must be calculated.
Amount of coupons for JAN 2005 : 4 X2 million =8.000 .000 couponsAmount of redeemed coupons : 8.000 .000 X10% = 800 .000 couponsFace Value : 1TLRedeemed coupon value : 1 TL X800 .000 = 8 00.000 TL Coupon processing cost : 0,1 TL X800 .000 = 8 0.000 TL Printing & Distribution cost : (20 TL X8.000 .000)/1000 =160.000 TL
TOTAL COST =8 00.000 TL+ 8 0.000 TL+ 160.000 TL=1.040.000 TL
Since gross margin per case is 52,8 TL, to reach the break-even point of this promotion, the amountthat Ülker must sell in excess of sales is;
1.040.000 TL/ 52 .8 TL =19.697 cas § s (appx. 20.000 cases )
2) Since we have a data that may have seasonality and trend components, we must build ourregression model using dummy variables and trend factor.
COEFFICIENTSY : Expected amount of cases to be soldint : Intercept of regression modelCP : Consumer promotion coefficientTP : Trade promotion coefficientJan_D : January dummy coeffitient...Nov_D : November dummy coefficientTRND : Trend component coefficient
VA IABLESX1
: Consumer promotion amountX2
: Trade promotion amountX3
: January dummy variableX4
: February dummy variable...X13
: November dummy variableX14
: Trend component variable
So our regression model should be in below format;
Y=int+(CP. X1)+ (TP. X2)+(Jan_D. X3)+(Feb _D. X4)+...+(Nov_D.X13)+(TRND.X14)
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G aduate School of Business
M K T G 9 0 1 2
Our current data shows that there are discontinuing valuesbetween the beginning of 1998 and theend of 2001 . In order to run a proper regression, discontinuing part of the data (Jan 1998 Dec2001) is deleted from the data series.
We assume that our sales data is affected by seasonality and trend components, so these issuesmust be examined by Excel Data Analysis / Regression Tool. According to our iterative calculationsincluding shifted effects of consumer and trade promotions 1, all possible regression models showthat there is no significant trend effect in existing data. This means that existing positive sales trendexists because of the positive trend in promotions. Therefore, trend variable is excluded from ourregression model.
In addition, we calculated both consumer and trend promotions shifting possibilities for 1 and 2 months, but all possible regression models resulted with smaller R 2 values. This also shows us thatthere is no significant shifted effect of consumer and trade promotions on sales amount. Theseresults can be seen in Exhibits 1 to 9.
The best possible regression model (R 2 = 0,93 - Exhibit1) has the following equation:
Y = 225.186,50 + (0,04 x CP) + (0,07 x TP) + (J an_D x 241.553,38) + (M ar_D x 107.144,37) +(Apr_D x 125.707,62) + (M ay_D x 201.766,33) + (Ju n_D x 104.040,00) + (Ju l_D x 167.069,63)(Se p _D x 209.899,83) + (Oc t_D x 97.483,01) + (N ov_D x 80.466,71)
In our example, we are looking for the sale expectation for January 2005 . So our regression modelbecomes as below;
Y =466.739,88 + (0,04 x CP)+ (0,07 x TP)
a. The variables that predict sales are amount of consumer promotions (in dollars ) and tradepromotions (in dollar ) and the dummy variable that is used for the month of January.
b. The potential promotion impact will be the delta of the regression model, with or withoutthe consumer promotions in Jan 2005 . (Trade promotion is constant, so we can assume thatit s zero, and we assume that the exchange rate for USD and TRL is 1,5 TL/ USD)
Without consumer promotion; Y= 466.740 casesWith consumer promotion; Y= 466.740 + 0,04 x (1.040.000 / 1,5) = 494.473 casesDifference = 27.733 cases
Since we have 52,8 TL margin for each case, our potential profit would be;
Potential Profit = 27.733 x 52 ,8 TL =1.464.302 TL
c. According to our calculation, Ülker Bar brand manager will spend 1.040.000 TL forpromotion for an expected additional profit of 1.464.302 TL. These figures show that heshould do the consumer promotion.
1 Shifted effect: Statistically, if consumer or trade promotions have a significant effect on previous months sales,we call this as a shifted effect of promotions to sales.
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G aduate School of Business
M K T G 9 0 1 3
Exhibit 1 Regression Model Without Shifting Eff ect
Shifting Effect Assumption: Consumer Prom. and Trade Prom. have no delayed effect
Regression R2 =0,93(Best Possible Model)
MonthSales in CASES
(©
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64 0 0 1 0 0 0 0 0 0 0 0 4May. 02 444 .404 $10 5.058 $47 8.880 0 0 0 1 0 0 0 0 0 0 0 5Ha# .02 386.986 $5.328 $457.172 0 0 0 0 1 0 0 0 0 0 0 6
Tem. 02 414 .314 $ 2.093 $709 .480 0 0 0 0 0 1 0 0 0 0 0 7A u.02 253.493 $6 .754 $4 5.380 0 0 0 0 0 0 0 0 0 1 0 8Eyl.02 484.365 $1 .807 .920 $28.080 0 0 0 0 0 0 1 0 0 0 0 9E
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i.02 305.989 $589.949 $111 .520 0 0 0 0 0 0 0 1 0 0 0 10Kas.02 315.407 $7 2.662 $267 .200 0 0 0 0 0 0 0 0 1 0 0 11Ara.02 182.784 $26.554 $354.304 0 0 0 0 0 0 0 0 0 0 0 1 2
ca. 03 655.748 $2.615.074 $664 .712 1 0 0 0 0 0 0 0 0 0 0 1 3u
.03 270 .483 $209 .798 $536.824 0 0 0 0 0 0 0 0 0 0 1 14Mar. 03 365.058 $27.552 $551.560 0 1 0 0 0 0 0 0 0 0 0 1 5
"
is. 03 313.135 $46 .147 $1 50.080 0 0 1 0 0 0 0 0 0 0 0 16May. 03 528.210 $7 .234 $580.800 0 0 0 1 0 0 0 0 0 0 0 17Ha# .03 379 .856 $6 5.376 $4 35.080 0 0 0 0 1 0 0 0 0 0 0 1 8
Tem. 03 472.058 $485.659 $361 .144 0 0 0 0 0 1 0 0 0 0 0 19A u.03 254.516 $ 385.483 $97 .844 0 0 0 0 0 0 0 0 0 1 0 20Eyl.03 551.354 $1 .611 .686 $30.372 0 0 0 0 0 0 1 0 0 0 0 21E
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Oca. 04 4 55.136 $1 .438.949 $ 32.532 1 0 0 0 0 0 0 0 0 0 0 25u
.04 247 .570 $101 .846 $ 23.468 0 0 0 0 0 0 0 0 0 0 1 26Mar. 04 6 22.204 $7 54 $4 .503.456 0 1 0 0 0 0 0 0 0 0 0 27Nis. 04 4 29.331 $6 2.213 $500 .904 0 0 1 0 0 0 0 0 0 0 0 28
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Tem. 04 4 51.779 $1 .514 .707 $46 .104 0 0 0 0 0 1 0 0 0 0 0 31A u.04 249 .482 $384.989 $9 2.252 0 0 0 0 0 0 0 0 0 1 0 32Eyl.04 744 .583 $28.512 $4 .869 .952 0 0 0 0 0 0 1 0 0 0 0 33E
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i.04 4 21.186 $176 .731 $376 .556 0 0 0 0 0 0 0 1 0 0 0 34Kas.04 397 .367 $1 .125.898 $376 .556 0 0 0 0 0 0 0 0 1 0 0 35Ara.04 269 .096 $ 345.029 $552.536 0 0 0 0 0 0 0 0 0 0 0 36
SIGNIFICAN% REGRESSI& N M& DELPARAME% ERS INSIGNIFICAN' PARAME' ERS
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Graduate School of Business
M K T G 9 0 1 4
Exhibit 2 Regression Model With Shifting Eff ect
Shifting Effect Assumption: Consumer Prom. none, Trade Prom.has 1 month delayed effect
Regression R2 =0,65
Month Sales in CASESS
T )U RV W Jan _ W Mar_ W Ma X _ W Jul _ W Se Y _ W AY r_ W Jun _ W
` ct _ W V o a _ W CP U Pb 1 Feb_ W Aug_ W
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Graduate School of Business
M K T G 9 0 1 5
Exhibit 3 Regression Model With Shifting Eff ect
Shifting Effect Assumption: Consumer Prom. none, Trade Prom.has 2 months delayed effect
Regression R2 =0,64
Month Sales in ASES Y
Jan_ Mar _ Ma z _ Jul_ Se { _ TR| Apr _ Jun _ Oct_ | o } _
~ Aug _ Feb _ T~ +2
Mar. 02 389 .320 0 1 0 0 0 1 0 0 0 0
13.406 0 0
0
is.02 376.569 0 0 0 0 0 2 1 0 0 0
133.195 0 0
315 .19 6May.02 444.4 04 0 0 1 0 0 3 0 0 0 0
105 .058 0 0
703.624 a .02 386.986 0 0 0 0 0 4 0 1 0 0
5.328 0 0
198 .464Tem.02 414.314 0 0 0 1 0 5 0 0 0 0
2.093 0 0
478.880A
u.02 25 3.493 0 0 0 0 0 6 0 0 0 0
6.754 1 0
457.172Eyl.02 484.365 0 0 0 0 1 7 0 0 0 0
1.80 7.920 0 0
709 .480E i.02 305 .989 0 0 0 0 0 8 0 0 1 0
589 .949 0 0
45.380Kas.02 315 .407 0 0 0 0 0 9 0 0 0 1
72.662 0 0
28 .080Ara.0 2 1 82 .784 0 0 0 0 0 10 0 0 0 0
26.554 0 0
111 .520 ca. 03 655 .748 1 0 0 0 0 11 0 0 0 0
2.615 .074 0 0
267.200
ub.03 270.483 0 0 0 0 0 12 0 0 0 0
209 .798 0 1
354.304Mar. 03 365.058 0 1 0 0 0 1 3 0 0 0 0
27.552 0 0
664.7 12 is.03 313.135 0 0 0 0 0 1 4 1 0 0 0
46.147 0 0
536.82 4May.03 528 .210 0 0 1 0 0 15 0 0 0 0
7.234 0 0
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65.376 0 0
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485 .659 0 0
580 .800A
u.03 254.516 0 0 0 0 0 18 0 0 0 0
385 .483 1 0
435.080
Eyl.03 551 .354 0 0 0 0 1 19 0 0 0 0
1.611 .686 0 0
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97.844Kas.03 320 .408 0 0 0 0 0 21 0 0 0 1
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30.372Ara.03 276.901 0 0 0 0 0 22 0 0 0 0
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8/3/2019 62707413 Ulker Chocolate Bars Assignment
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Graduate School of Business
M K T G 9 0 1 6
Exhibit 4 Regression Model With Shifting Eff ect
Shifting Effect Assumption: Consumer Prom.has 1 month delayed effect, Trade Prom. none
Regression R2 =0,91
MonthSales in
CASES (Y) TP Jan_D Mar _D A-
r _D Ma®
_D Jun_D Jul_D Se-
_D Oct_D Nov_D TRND CP+1 Feb _D Aug _D¯ ub.02 2 63.467
°
315 .196 0 0 0 0 0 0 0 0 0 2°
2.633.77 9 1 0Mar. 02 389 .320
°
703.624 0 1 0 0 0 0 0 0 0 3°
253.526 0 0Nis.02 376.569
°
198 .464 0 0 1 0 0 0 0 0 0 4°
13.406 0 0May.02 444.4 04
°
478.880 0 0 0 1 0 0 0 0 0 5°
133.195 0 0± az.02 386.98 6
°
457.172 0 0 0 0 1 0 0 0 0 6°
105 .058 0 0Tem.02 414.314
°
709 .480 0 0 0 0 0 1 0 0 0 7°
5.328 0 0A
²
u.0 2 2 5 3.493°
45.380 0 0 0 0 0 0 0 0 0 8°
2.093 0 1Eyl.02 484.36 5
°
28 .080 0 0 0 0 0 0 1 0 0 9°
6.754 0 0Eki.02 305 .989
°
111 .520 0 0 0 0 0 0 0 1 0 10°
1.807.920 0 0Kas.02 315 .407
°
267.200 0 0 0 0 0 0 0 0 1 11°
589 .949 0 0Ara.02 182 .784
°
354.304 0 0 0 0 0 0 0 0 0 12°
72.662 0 0³
ca. 03 655 .748°
664.7 12 1 0 0 0 0 0 0 0 0 1 3°
26.554 0 0¯ ub.03 270.483
°
536.824 0 0 0 0 0 0 0 0 0 1 4°
2.615 .074 1 0Mar. 03 365.058
°
551 .560 0 1 0 0 0 0 0 0 0 15°
209 .798 0 0Nis.03 313.135
°
150 .080 0 0 1 0 0 0 0 0 0 1 6°
27.552 0 0May.03 528 .210
°
580 .800 0 0 0 1 0 0 0 0 0 1 7°
46.147 0 0± az.03 379.85 6
°
435.080 0 0 0 0 1 0 0 0 0 18°
7.234 0 0Tem.03 472.058
°
361.144 0 0 0 0 0 1 0 0 0 19°
65.376 0 0A
²
u.03 254.51 6°
97.844 0 0 0 0 0 0 0 0 0 20°
485 .659 0 1Eyl.03 551 .354
°
30.372 0 0 0 0 0 0 1 0 0 21°
385 .483 0 0Eki.03 335.82 6
°
150 .324 0 0 0 0 0 0 0 1 0 22°
1.611 .686 0 0Kas.03 320 .408
°
293.044 0 0 0 0 0 0 0 0 1 2 3°
440.208 0 0Ara.03 276.901
°
162.788 0 0 0 0 0 0 0 0 0 2 4°
47.309 0 0³ ca. 04 455 .136
°
32.532 1 0 0 0 0 0 0 0 0 25°
514.426 0 0¯ ub.04 247.570
°
23.468 0 0 0 0 0 0 0 0 0 2 6°
1.438.949 1 0Mar. 04 622 .20 4
°
4.503.456 0 1 0 0 0 0 0 0 0 2 7°
101 .846 0 0Nis.04 429 .331
°
500 .904 0 0 1 0 0 0 0 0 0 28°
754 0 0May.04 453.15 6
°
0 0 0 0 1 0 0 0 0 0 29°
62.213 0 0± az.04 320 .10 3
°
0 0 0 0 0 1 0 0 0 0 30°
1.600 .939 0 0Tem.04 451 .779
°
46.104 0 0 0 0 0 1 0 0 0 31°
854.904 0 0A
²
u.04 249.482°
92 .252 0 0 0 0 0 0 0 0 0 32°
1.514.707 0 1Eyl.04 744.58 3
°
4.869.952 0 0 0 0 0 0 1 0 0 33°
384.989 0 0Eki.04 421 .18 6
°
376.556 0 0 0 0 0 0 0 1 0 34°
28 .512 0 0Kas.04 397.367
°
376.556 0 0 0 0 0 0 0 0 1 35°
176.73 1 0 0Ara.04 269.09 6
°
552 .536 0 0 0 0 0 0 0 0 0 36°
1.125 .898 0 0
INSIGNIFICANTPARAMETERSSIGNIFICANT REGRESSIONMODEL PARAMETERS
SUMMA Yµ UTPUT
Regre ¶ ¶
· o ¸ St ¹ tisticsMu º tip º e » ¼ , ½ ¾
» Squ ¿ re ¼ , ½ À
Á
dÂ
usted » Squ ¿ re ¼ , Ã Ã
St ¿ nd ¿ rdErrÄ rÅ Å
Æ ¼ Ç Ã ,Å
È
ObserÉ
¿ ti Ä ns Ê Ë , ¼ ¼
Á
NOVÁ
Ì
Í
SS Î S F Si g ¸ i Í
ic ¹ ¸ ce F »
eÏ ress i Ä
nÀ ¼
,¼ ¼
Å
½ Ç Æ Ê ½ ½ Æ Ã À È Æ Ë Ç Ã ,
È È
Å
½ Æ Ç Ê ½ Æ ½ Ã À Æ È Ë Ç ,
Ã Ã Ç Ë ,Å
¼ ¼ ,
¼ ¼
» es idu ¿ º Ç
Å
, ¼ ¼
Å
¾ Æ Ë Ç
Å
Æ À
Å Å
Æ Ë
Å
È , ¾
Å
À Æ ½ Ê Ã Æ Ë ¼ ¾ Æ ¼ Ç Ç , Ã Ç
TÄ t ¿ l Ê
Å
, ¼ ¼ Ë Ê Ã Æ ½ Ç Ê Æ ½ ¾ Ç Æ ¼ È ¾ ,Å
¼
Ð oeÍ Í
ici e ¸ ts St ¹ ¸ Ì ¹ r Ì Ñ rror t St ¹ t P-v ¹ Ò Ó e Lower 95% UÔ Ô er 95% Lower 95 , Õ % UÔ Ô er 95 , Õ %
Inter Ö ep t Ç Ê Ã Æ
Å
È ¼ , ¾ À À
Å
Æ Ã À ½ , Ã
Å
À ¾ , ¼ ½ ¼ , ¼ ¼ Ç ¼ È Æ Ã Ã Ê , ½ ¾ Ç ¾ ½ Æ ¼ Ë È , Ç ¾ Ç ¼ È Æ Ã Ã Ê , ½ ¾ Ç ¾ ½ Æ ¼ Ë È , Ç ¾
TP ¼ , ¼ ¾ ¼ , ¼ À ¾ , Ë ¾ ¼ , ¼ ¼ ¼ , ¼
Å
¼ , ¼ È ¼ , ¼
Å
¼ , ¼ È
J¿ n_D Ç ½ È Æ Ë Ê È , Ë Ë Ê
Å
Æ
Å
Ê ¼ ,Å
½ Ã , ¾
Å
¼ , ¼ ¼ Ç Ç ¾ Æ
Å
È ¾ , Ë À Ê ¾ Ã Æ Ë ½ Ã , ¾ ¼ Ç Ç ¾ Æ
Å
È ¾ , Ë À Ê ¾ Ã Æ Ë ½ Ã , ¾ ¼
Ma r_D À À Ê Æ Ê Ã Ë ,Å
¾ Ê Ç Æ ¾ Ç ½ , À Ê Ê ,Å
È ¼ , ¼ ¼
Å
¾ Æ ¼
Å
Ç , Ç Ë À Ã ¼ Æ È Ç Ã , ¾ Ã
Å
¾ Æ ¼
Å
Ç , Ç Ë À Ã ¼ Æ È Ç Ã , ¾ Ã
Á
pr_D À À Ã Æ È Ë ¾ , ½ È Ç ½ Æ Ê Ë
Å
, Ê È
Å
, ¼ Ë ¼ , ¼ ¼ Ë Ã Æ À È Ç , Ë
Å
À È ½ Æ Ê
Å
À ,Å
À Ë Ã Æ À È Ç , Ë
Å
À È ½ Æ Ê
Å
À ,Å
À
May _D Ç À È Æ ¼ ½ Ë , Ë Ê Ç ½ Æ Ê ¾ È ,Å Å
È , Ê ½ ¼ , ¼ ¼ À Ë ¾ Æ
Å
Ã
Å
, À À Ç È È Æ È ¼ ¾ , ½ ¾ À Ë ¾ Æ
Å
Ã
Å
, À À Ç È È Æ È ¼ ¾ , ½ ¾
Jun_D À ¼ È Æ Ç ¾
Å
, ½
Å
Ç ½ Æ Ê Ë ¾ , ¼ Ë Ê , ¾ Ë ¼ , ¼ ¼
Å
¾ Æ ¾ È È , ¼ Ê À ¾ È Æ Ã Ë Ç , Ã Ë
Å
¾ Æ ¾ È È , ¼ Ê À ¾ È Æ Ã Ë Ç , Ã Ë
Jul _D À Ã ¾ Æ Ã Ç ½ , À ¾ Ç ½ Æ Ê È Ê , ¼ È ¾ , Ê ¾ ¼ , ¼ ¼ À Ç ¾ Æ Ç ¼ ¾ , À À Ç
Å
È Æ
Å
Ë Ç , Ç ¼ À Ç ¾ Æ Ç ¼ ¾ , À À Ç
Å
È Æ
Å
Ë Ç , Ç ¼
Sep_D Ç ¾ Ê Æ Ê Ã Ë , Ã ½ Ê À Æ ¾ È Ç , Ã ¼ Ã , Ê Ç ¼ , ¼ ¼ À ½ Ã Æ ¼ À ¾ ,Å
Ê Ê Ç Ã Æ È Ë Ë , Ê
Å
À ½ Ã Æ ¼ À ¾ ,Å
Ê Ê Ç Ã Æ È Ë Ë , Ê
Å
OÖ t _D À ¼
Å
Æ ¼ ¼ ¼ , Ë Ã Ç ½ Æ Ê Ë Ê , Ê Ã Ê , Ë
Å
¼ , ¼ ¼
Å
Ê Æ
Å
À Ã , À Ã À ¾
Å
Æ Ë Ã Ç , ½ Ã
Å
Ê Æ
Å
À Ã , À Ã À ¾
Å
Æ Ë Ã Ç , ½ Ã
NÄ
É _D Ã Ã Æ Ë À ¾ , À È Ç ½ Æ Ê Ë Ã , Ê Ê Ê , ¼ Ç ¼ , ¼ À Ç È Æ ½ Ç Ê , Ë Ë À
Å
½ Æ À ¼ Ã , È ½ Ç È Æ ½ Ç Ê , Ë Ë À
Å
½ Æ À ¼ Ã , È ½
8/3/2019 62707413 Ulker Chocolate Bars Assignment
http://slidepdf.com/reader/full/62707413-ulker-chocolate-bars-assignment 8/12
Graduate School of Business
M K T G 9 0 1 7
Exhibit 5 Regression Model With Shifting Eff ect
Shifting Effect Assumption:Both Consumer and Trade Promotionshave 1 month delayed effect
Regression R2 =0,65
MonthSa les in
× Ø
SE S Ù
Ú
)
Û anÜ
Ý MarÜ
Ý Ma Þ
Ü
Ý
Û ulÜ
Ý SepÜ
Ý
ß RN Ý
Ø prÜ
Ý
Û unÜ
Ý
à ctÜ
Ý No á
Ü
Ý FebÜ
Ý
×
â
ã 1 Ø ugÜ
Ý
ß
â
ã 1
uä .0 2 26 3.46 7 0 0 0 0 0 2 0 0 0 0 1 $2 .6 33. 77 9 0 $0
Mar .02 38 9.3 2 0 0 1 0 0 0 3 0 0 0 0 0 $25 3. 526 0 $31 5 .19 6
Nis .02 376 .56 9 0 0 0 0 0 4 1 0 0 0 0 $13. 4 06 0 $7 03. 624May .02 4 44 .4 04 0 0 1 0 0 5 0 0 0 0 0 $133.19 5 0 $19 8 .464
Ha å .02 386 .986 0 0 0 0 0 6 0 1 0 0 0 $10 5 .0 58 0 $4 78 .88 0Te m.0 2 4 14 .31 4 0 0 0 1 0 7 0 0 0 0 0 $5 .3 28 0 $45 7 .172
Aæ
u .0 2 25 3.4 93 0 0 0 0 0 8 0 0 0 0 0 $2 .093 1 $7 09. 48 0Eyl.02 4 84 .365 0 0 0 0 1 9 0 0 0 0 0 $6 .754 0 $45 .3 8 0E
ç i.02 30 5 .98 9 0 0 0 0 0 1 0 0 0 1 0 0 $1.8 07 .9 2 0 0 $28 .0 8 0
Kas.0 2 31 5 .4 07 0 0 0 0 0 1 1 0 0 0 1 0 $58 9.9 4 9 0 $111. 52 0Ara.02 182 .784 0 0 0 0 0 1 2 0 0 0 0 0 $7 2 .662 0 $26 7 .2 00
Oca .03 655 .748 1 0 0 0 0 1 3 0 0 0 0 0 $26 .554 0 $354 .30 4
uä .03 2 70.48 3 0 0 0 0 0 1 4 0 0 0 0 1 $2 .6 15 .0 74 0 $664 .712
Mar . 03 3 65 .058 0 1 0 0 0 1 5 0 0 0 0 0 $2 09. 798 0 $5 36 .824
Nis .03 313.13 5 0 0 0 0 0 1 6 1 0 0 0 0 $2 7 .552 0 $55 1.56 0May .03 528 .2 10 0 0 1 0 0 1 7 0 0 0 0 0 $46 .1 4 7 0 $15 0.0 8 0Ha å . 03 3 79.856 0 0 0 0 0 1 8 0 1 0 0 0 $7 .2 34 0 $58 0.8 00
Te m.03 4 72 .058 0 0 0 1 0 1 9 0 0 0 0 0 $65 .3 76 0 $4 35 .08 0
Aæ
u .03 254 .5 16 0 0 0 0 0 2 0 0 0 0 0 0 $485 .65 9 1 $36 1.1 44Eyl.03 55 1.3 54 0 0 0 0 1 2 1 0 0 0 0 0 $385 .48 3 0 $97 .844
E ç i.03 33 5 .826 0 0 0 0 0 22 0 0 1 0 0 $1.6 11. 686 0 $30.3 72
Kas. 03 3 2 0.4 08 0 0 0 0 0 2 3 0 0 0 1 0 $44 0. 2 08 0 $15 0.3 24
Ara.03 2 76 .901 0 0 0 0 0 24 0 0 0 0 0 $4 7 .309 0 $2 93.0 44
Oca .04 4 55 .13 6 1 0 0 0 0 25 0 0 0 0 0 $5 14 .426 0 $162 .788
u ä .0 4 24 7 .5 70 0 0 0 0 0 26 0 0 0 0 1 $1.4 38 .9 4 9 0 $32 .5 32
Mar .04 6 22 .2 04 0 1 0 0 0 2 7 0 0 0 0 0 $101. 846 0 $2 3. 468
Nis .04 42 9.331 0 0 0 0 0 28 1 0 0 0 0 $7 54 0 $4 .5 03. 456
May .04 45 3.1 56 0 0 1 0 0 2 9 0 0 0 0 0 $62 .2 13 0 $5 00.90 4
Ha å .04 32 0.103 0 0 0 0 0 30 0 1 0 0 0 $1.6 00.939 0 $0Te m.0 4 45 1.77 9 0 0 0 1 0 3 1 0 0 0 0 0 $854 .90 4 0 $0A
æ
u .0 4 24 9.482 0 0 0 0 0 3 2 0 0 0 0 0 $1.5 14 .707 1 $46 .10 4Eyl.04 744 .58 3 0 0 0 0 1 3 3 0 0 0 0 0 $384 .9 8 9 0 $92 .252
E ç i.04 42 1.1 86 0 0 0 0 0 3 4 0 0 1 0 0 $28 .5 12 0 $4 .86 9.9 52
Kas.0 4 39 7 .36 7 0 0 0 0 0 3 5 0 0 0 1 0 $176 .731 0 $376 .556
Ara.04 26 9.09 6 0 0 0 0 0 3 6 0 0 0 0 0 $1.1 25 .8 98 0 $376 .556
Sè GNè Fè é
ê Në REGRESSè ì N Mì í ELî
ê Rê MEë ERS è NSè GNè Fè é
ê Në î
ê Rê MEë ERS
Sï
MMAð
ñ
OUTPUT
R ò ó r ò ss i o ô õ
t ö t i st i csM u lt ip l ÷ ø ù ,8 ú
ø
û ü u aý ÷ ù
,65þ
djusted ø û ü u a ý e 0 ,5 ÿ
û tand a ý d ý ý or 80.86 ÿ ,78¡ ¢ ser va t ions 3 5,00
ANOVA
£ f õ õ
¤
õ
¥
õ
i ó ô i f i c ö nc ò ¥
Regress ion 5,00 3 4 ÿ .266.242. ú 46,4 0 6 ÿ .853.248.42 ÿ ,28 ú 0,68 0,00
Res idu al 2 ÿ ,00 1 8 ÿ .657.719 .930 ,00 6.539 .921.376,90Tot al 34,00 538.923.962.076,4 0
¦ oe ff i ci entsõ
t ö n £ ö r £ § rr o r t õ
t ö t ¨ - © ö lue Lo e r
er
Lo er
e r
Intercept 31 2.855,00 1 7.647, 23 1 7,73 0 ,00 276.76 2,36 348.947,64 276.76 2,36 348.947,64Jan _ 242.587,00 59.844,6 8 4,05 0,00 1 20.190 ,89 3 64.983,11 1 20.190 ,89 3 64.983,11
M ar _ 146.005,67 4 9.913 ,91 2,93 0 ,01 43.920,26 248.091 ,08 43.920,26 248.091 ,08M a _
162.401 ,67 4 9.913 ,91 3 ,25 0,00 60.316,26 264.4 87,08 60.316,26 264.4 87,08Ju l_ 133 .195,33 49.913 ,91 2,67 0,01 31 .109 ,92 235.280,74 31 .109 ,92 235.280,74
û ep _ 280.579,00 49.913 ,91 5,62 0,00 1 78.493 ,59 3 82.664,4 1 1 78.493 ,59 3 82.664,4 1
8/3/2019 62707413 Ulker Chocolate Bars Assignment
http://slidepdf.com/reader/full/62707413-ulker-chocolate-bars-assignment 9/12
Graduate School of Business
M K T G 9 0 1 8
Exhibit 6 Regression Model With Shifting Eff ect
Shifting Effect Assumption:Con. Prom. has 1 month, Trade Prom. has 2 months delayed effect
Regression R2 =0,65
MonthSa les in
C
SES (Y)Jan_ ! Mar _ ! Ma " _ ! Jul_ ! Se # _ ! TR$ !
# r _ ! Jun_ !
% ct_ ! $ o & _ ! CP+ ' Feb _ ! TP+2 ug _ !
Mar. 02(
89 .(
20 0 1 0 0 0 1 0 0 0 0)
20 ( .0
21
0)
0 0Nis.02
( 2 1
.0 1
9 0 0 0 0 0 2 1 0 0 0)
1(
.3
01
0)
(
10
.191
0May. 02
3 3 3 .3
03
0 0 1 0 0(
0 0 0 0)
1( ( .19
0
0)
2
0( .1
23
04
az.02(
81 .98
1
0 0 0 0 03
0 1 0 0)
100 .0
0
8 0)
198 .3 1 3
0Tem.02
3
13
.(
13
0 0 0 1 00
0 0 0 0)
0
.(
28 0)
3 2
8 .880 0A
5
u.02 20 ( .3
9(
0 0 0 0 01
0 0 0 0)
2 .09(
0)
3 0 2 .12
2 1Eyl.02
3
83
.( 1 0
0 0 0 0 12
0 0 0 0)
1
.2 0 3
0)
2
09 .3
80 0Eki.02
(
00
.989 0 0 0 0 0 8 0 0 1 0)
1 .802
.920 0)
3 0
.(
80 0Kas.02
(
10
.3
02
0 0 0 0 0 9 0 0 0 1)
0
89 .93
9 0)
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83
0 0 0 0 0 1 0 0 0 0 0)
2
2 .1 1
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8 1 0 0 0 0 1 1 0 0 0 0)
21 .0 0 3
0)
21 2 .200 0
6
ub. 0(
22
0 .3
8(
0 0 0 0 0 1 2 0 0 0 0)
2 .1
10
.02 3
1)
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.(
03
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( ( 1 0 .00
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0 0 0 0)
209 .2
98 0)
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1( .1
( 0
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2 0)
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( 0
28 .210 0 0 1 0 0 10
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0)
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0 04 az.0
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9 .80 1
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0)
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80 .800 0A
5
u.0(
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3 3
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3 1
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0 1 0 0 0 20
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101 .83 1
0)
(
2 .0 (
2 0Nis.0
3 3
29 .( (
1 0 0 0 0 0 21
1 0 0 0)
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0)
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8 0May. 0
3 3 0 (
.10 1
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0)
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.0
0(
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04 az.0
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20 .10(
0 0 0 0 0 2 8 0 1 0 0)
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9 0)
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5
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02
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(
83 .989 0
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28 .0
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SIG7 IFIC8
7 T REGRESSI9 7 M 9 @ EA P8 R8 METERS I7 SIG7 IFIC8
7 TP8 R8 METERS
SB MMARY OB TPB T
R eg r eC C ion St a t i C t icC
M ultip lD
R 0E 80R Squ are 0E 64Ad just e d RSqu are 0E 58
Stand ar d Error 81.743E 63F bs erva tio ns 34,00
AG F
H
A
d f SS MS F Si g ni f ica n ce F
Re gre ssio n 5,00 335.703.829.762,64 67 .140.765 .952,5 3 10,05 0,00Re sidu a l 28, 00 187 .096.586 .658,8 0 6.682 .020.952, 10To ta l 33,00 522 .800.416.421,44
Coeff ici en t C St a n da r d Error t St a t P-v a l u e Lo I er 95 P Q
R R er 95 P Lo I er 95S 0 P Q
R R er 95S 0 P
Int er ce pt 3 15.324,4 0 18.278,4 3 17,25 0,00 277 .882,7 3 352 .766, 07 277 .882,7 3 352 .766, 07
Ja nT
U 240.117,6 0 60.622,7 0 3,96 0,00 115.937,6 3 364 .297,57 115.937,6 3 364 .297,57M ar_D 143.536,27 5 0.610,68 2,84 0,01 39.864, 98 247 .207,55 39.864, 98 247 .207,55M ay_D 159.932,27 5 0.610,68 3,16 0,00 56 .260,98 26 3.603,55 56 .260,98 26 3.603,55
Ju l _D 130.725, 93 50.610,68 2,58 0,02 27 .054,65 2 34.397,22 27 .054, 65 2 34.397,22
Se p _D 278 .109,60 50.610,68 5,5 0 0,00 174 .438,31 381.780,89 174 .438, 31 381.780,89
8/3/2019 62707413 Ulker Chocolate Bars Assignment
http://slidepdf.com/reader/full/62707413-ulker-chocolate-bars-assignment 10/12
Graduate School of Business
M K T G 9 0 1 9
Exhibit 7 Regression Model With Shifting Eff ect
Shifting Effect Assumption: Con. Prom. has 2 months delayed effect, Trade Prom. none
Regression R2 =0,91
MonthSales in
V W
SES X
Y
` TPa
an_D Mar _DW
b
r _D Mac
_Da
un_Da
ul_D Seb
_Dd
ct_De
of
_D TRe
DV
P+2W
ug _D Feb _DMar. 02
g h
9.g
20i
p
0g .q
2r
0 1 0 0 0 0 0 0 0 1i
2.q g g .p p
9 0 0Nis.02
g p q
.s q
9i
19h
.r q r
0 0 1 0 0 0 0 0 0 2i
2s g
.s
2q
0 0May.02
r r r
.r
0r
i
r p h
.h h
0 0 0 0 1 0 0 0 0 0g
i
1g
.r
0q
0 0t
a u .02g h q .9
h q
i
r s p .1p
2 0 0 0 0 1 0 0 0 0r
i
1g g .19
s
0 0Tem.02
r
1r
.g
1r
i
p
09 .r h
0 0 0 0 0 0 1 0 0 0s
i
10s
.0s h
0 0A
v
u.02 2s g .r
9g
i
r s .g h
0 0 0 0 0 0 0 0 0 0q
i
s .g
2h
1 0Eyl.02
r h r .g q s
i
2h .0
h
0 0 0 0 0 0 0 1 0 0p
i
2.09g
0 0Eki.02
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Ix SIGx IFIy
x TP
R
METERSSIGx IFIy
x T REGRESSI
x MODE P
R
METERS
S MMARY O TP T
Regre ss ion St a t i st i sM ult iple R ,
R Squar e ,
Ad just ed R Squar e ,
Stand ar d Error 44 . 45 ,42
Obse rva t ions 4 ,
A OVA
df SS M S F Signifi an e F Regre ss ion
, 476 . . 22 .266 ,
4 47 .633 . 32 .226 ,68 23 ,58 0 ,00
Re sidu a l 23 ,00 46 .462 .094 . 54 ,60 2 .020 .091 .050 ,20
To ta l 33 ,00 522 .800 .416 .421 ,44
C oeffi ien t s St andard Error t St a t P-val ue Low er 95% pp er 95% Low er 95 , % pp er 95 , %Inte rcep t 237 .547 ,67 16 .018 ,83 14 ,83 0 ,00 204 .410 ,20 270 .685 ,14 204 .410 ,20 270 .685 ,14
TP 0 ,06 0 ,01 6 ,42 0 ,00 0 ,04 0 ,07 0 ,04 0 ,07
Jan_D 298 .468 ,41 35 .546 ,59 8 ,40 0 ,00 224 .934 ,69 372 .002 ,12 224 .934 ,69 372 .002 ,12M ar _D 114 .351 ,96 33 .762 ,09 3 ,39 0 ,00 44 .509 ,75 184 .194 ,17 44 .509 ,75 184 .194 ,17
Apr _D 119 .686 ,34 30 .431 ,28 3 ,93 0 ,00 56 .734 ,44 182 .638 ,25 56 .734 ,44 182 .638 ,25M a _D 218 .026 ,49 30 .446 ,01 7 ,16 0 ,00 155 .044 ,12 281 .008 ,86 155 .044 ,12 281 .008 ,86
Jun_D 108 .194 ,63 30 .433 ,30 3 ,56 0 ,00 45 .238 ,56 171 .150 ,71 45 .238 ,56 171 .150 ,71
Jul_D 187 .760 ,55 30 .452 ,10 6 ,17 0 ,00 124 .765 ,58 250 .755 ,52 124 .765 ,58 250 .755 ,52
Sep_D 264 .346 ,11 32 .793 ,34 8 ,06 0 ,00 196 .507 ,91 332 .184 ,30 196 .507 ,91 332 .184 ,30
Oct _D 104 .928 ,35 30 .428 ,71 3 ,45 0 ,00 41 .981 ,77 167 .874 ,93 41 .981 ,77 167 .874 ,93
Nov _D 89 .446 ,20 30 .435 ,93 2 ,94 0 ,01 26 .484 ,68 152 .407 ,72 26 .484 ,68 152 .407 ,72
8/3/2019 62707413 Ulker Chocolate Bars Assignment
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Graduate School of Business
M K T G 9 0 1 1 0
Exhibit 8 Regression Model With Shifting Eff ect
Shifting Effect Assumption: Con. Prom. has 2 months, Trade Prom. has 1 month delayed effect
Regression R2 =0,64
MonthSa les in
ASES
an
D Mar
D May
D
ul
D Sep
D
R
D Apr
D
un
D
ct
D
o
D
j
k
1l
eb
D
j
k
2 Aug
DMar. 02 3 8 9 .320 0 1 0 0 0 1 0 0 0 0 $31 5 .19 6 0 $2 .633 .77 9 0Nis.02 3 76 .56 9 0 0 0 0 0 2 1 0 0 0 $7 03 .6 24 0 $25 3 .5 26 0
May. 02 444 .4 04 0 0 1 0 0 3 0 0 0 0 $19 8 .464 0 $13 .4 06 0Ha m .02 3 86 .986 0 0 0 0 0 4 0 1 0 0 $478 .88 0 0 $133 .19 5 0
Tem.02 4 14 .31 4 0 0 0 1 0 5 0 0 0 0 $457 .17 2 0 $10 5 .058 0A u.02 2 5 3 .4 93 0 0 0 0 0 6 0 0 0 0 $7 09 .48 0 0 $5 .32 8 1Eyl.02 484 .365 0 0 0 0 1 7 0 0 0 0 $45 .38 0 0 $2 .093 0E
n i.0 2 3 0 5 .98 9 0 0 0 0 0 8 0 0 1 0 $28 .08 0 0 $6 .754 0
Kas.0 2 3 1 5 .4 07 0 0 0 0 0 9 0 0 0 1 $111 .5 20 0 $1 .8 07 .920 0Ara.02 1 8 2 .784 0 0 0 0 0 10 0 0 0 0 $267 .200 0 $58 9 .94 9 0
O ca .03 655 .748 1 0 0 0 0 11 0 0 0 0 $354 .30 4 0 $7 2 .66 2 0u o .03 2 7 0 .48 3 0 0 0 0 0 12 0 0 0 0 $664 .7 12 1 $26 .554 0
Mar. 03 3 65 .058 0 1 0 0 0 13 0 0 0 0 $5 36 .8 24 0 $2 .615 .074 0Nis.0 3 3 13 .13 5 0 0 0 0 0 1 4 1 0 0 0 $55 1 .56 0 0 $209 .7 98 0
May. 03 5 28 .210 0 0 1 0 0 1 5 0 0 0 0 $15 0 .08 0 0 $27 .55 2 0Ha m .03 3 7 9 .856 0 0 0 0 0 1 6 0 1 0 0 $58 0 .8 00 0 $46 .147 0
Tem.03 47 2 .058 0 0 0 1 0 1 7 0 0 0 0 $4 35 .08 0 0 $7 .23 4 0A u.03 2 54 .5 16 0 0 0 0 0 1 8 0 0 0 0 $36 1 .144 0 $65 .376 1
Eyl.03 55 1 .354 0 0 0 0 1 19 0 0 0 0 $97 .844 0 $485 .65 9 0E n i.0 3 3 3 5 .8 26 0 0 0 0 0 20 0 0 1 0 $30 .37 2 0 $385 .48 3 0
Kas.0 3 3 20 .4 08 0 0 0 0 0 21 0 0 0 1 $15 0 .32 4 0 $1 .611 .686 0Ara.03 2 76 .901 0 0 0 0 0 22 0 0 0 0 $293 .044 0 $44 0 .20 8 0
O ca .04 4 55 .13 6 1 0 0 0 0 23 0 0 0 0 $16 2 .788 0 $47 .309 0u o .04 247 .57 0 0 0 0 0 0 2 4 0 0 0 0 $32 .5 32 1 $514 .4 26 0
Mar. 04 6 22 .20 4 0 1 0 0 0 2 5 0 0 0 0 $23 .468 0 $1 .4 38 .94 9 0Nis.04 4 29 .331 0 0 0 0 0 2 6 1 0 0 0 $4 .5 03 .456 0 $101 .846 0
May. 04 45 3 .156 0 0 1 0 0 2 7 0 0 0 0 $5 00 .90 4 0 $754 0Ha m .04 320 .103 0 0 0 0 0 2 8 0 1 0 0 $0 0 $6 2 .213 0
Tem.04 45 1 .77 9 0 0 0 1 0 29 0 0 0 0 $0 0 $1 .600 .939 0A u.04 24 9 .48 2 0 0 0 0 0 30 0 0 0 0 $46 .10 4 0 $854 .90 4 1Eyl.04 7 44 .58 3 0 0 0 0 1 31 0 0 0 0 $92 .25 2 0 $1 .5 14 .7 07 0E n i.04 4 21 .186 0 0 0 0 0 32 0 0 1 0 $4 .86 9 .95 2 0 $384 .98 9 0
Kas.04 39 7 .367 0 0 0 0 0 33 0 0 0 1 $376 .556 0 $28 .5 12 0Ara.04 26 9 .09 6 0 0 0 0 0 3 4 0 0 0 0 $376 .556 0 $176 .7 31 0
S G A
REGRESS M DEL ARAME ERS S G A
ARAME ERS
SUMMARYOUTPUT
Re re ss ion St a ti sti csMultiple R 0,80RSquare 0 ,64
d justed RSquare 0 ,58Standard Error 81.743,63Observations 34,00
NO
d f SS MS F Si nifi canc e F Regre ssion 5,00 335.703.829.762,64 67.140.765.952,53 10,05 0 ,00Residu al 28,00 187.096.586.658,80 6.682.020.952,10Total 33,00 522 .800.416.421,44
C oeffi cient s St anda r d E rror t St a t P-v a l ue Lo wer 95 z U pp er 95 z Lower 95{ 0 z U pp er 95{ 0 z
| ntercept 315.324,40 18 .278,43 17,25 0 ,00 277.882,73 352.766,07 277.882,73 352.766,07Jan _D 240.117,60 60.622,70 3,96 0,00 115 .937,63 364.297,57 115.937,63 364.297,57Mar _D 143.536,27 50.610,68 2,84 0,01 39.864,98 247.207,55 39.864,98 2 47.207,55May _D 159.932,27 50.610,68 3,16 0,00 56.260,98 263.603,55 56.260,98 2 63.603,55Jul _D 130.725,93 50.610,68 2,58 0 ,02 27.054,65 234.397,22 27.054,65 234.397,22Sep _D 278.109,60 50 .610,68 5,50 0 ,00 174.438,31 381.780,89 174.438,31 381.780,89
8/3/2019 62707413 Ulker Chocolate Bars Assignment
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Graduate School of Business
M K T G 9 0 1 1 1
Exhibit 9 Regression Model With Shifting Eff ect
Shifting Effect Assumption: Both Consumer and Trade Promotions have 2 months delayed effect
Regression R2 =0,64
Month Sale s in
CASES (}
)
~ an
D Mar
D Ma
D ~ ul
D Se
D TRND A r
D ~ un
D Oct
D N ov
D TP+2 CP+2 Feb
D Aug
D
Mar.02 389 .320 0 1 0 0 0 1 0 0 0 0
0
2 .633.77 9 0 0
Nis.02 376. 569 0 0 0 0 0 2 1 0 0 0
315 .19 6
25 3.52 6 0 0May.02 444.4 04 0 0 1 0 0 3 0 0 0 0
703.6 24
13.4 06 0 0
az. 02 386.98 6 0 0 0 0 0 4 0 1 0 0
198 .464
133. 195 0 0Tem.02 414.3 14 0 0 0 1 0 5 0 0 0 0
478 .880
105 .058 0 0A
u.0 2 2 5 3.4 93 0 0 0 0 0 6 0 0 0 0
457.172
5 .328 0 1Eyl.02 484.365 0 0 0 0 1 7 0 0 0 0
709 .480
2 .09 3 0 0
Eki.02 305 .989 0 0 0 0 0 8 0 0 1 0
45 .380
6.7 54 0 0Kas.02 315 .407 0 0 0 0 0 9 0 0 0 1
28 .080
1 .80 7.920 0 0Ara.02 182 .784 0 0 0 0 0 10 0 0 0 0
111 .520
589 .949 0 0Oca.03 655 .74 8 1 0 0 0 0 11 0 0 0 0
267. 200
72 .66 2 0 0ub.03 270 .483 0 0 0 0 0 12 0 0 0 0
354.3 04
26.55 4 1 0Mar.03 36 5 .058 0 1 0 0 0 1 3 0 0 0 0
664.7 12
2 .615 .074 0 0Nis.03 313.135 0 0 0 0 0 1 4 1 0 0 0
536. 82 4
209 .798 0 0
May.03 528 .210 0 0 1 0 0 15 0 0 0 0
551 .560
27.552 0 0
az. 03 37 9 .85 6 0 0 0 0 0 1 6 0 1 0 0
150 .080
46. 147 0 0Tem.03 47 2 .058 0 0 0 1 0 1 7 0 0 0 0
580 .800
7.234 0 0A
u.03 25 4.51 6 0 0 0 0 0 18 0 0 0 0
435 .080
65 .376 0 1Eyl.03 551 .354 0 0 0 0 1 19 0 0 0 0
361 .144
485 .659 0 0Eki.03 33 5 .82 6 0 0 0 0 0 20 0 0 1 0
97.844
385 .483 0 0Kas.03 320 .408 0 0 0 0 0 21 0 0 0 1
30 .37 2
1 .611 .686 0 0
Ara.03 276. 901 0 0 0 0 0 22 0 0 0 0
150 .324
44 0 .208 0 0Oca.04 455 .136 1 0 0 0 0 2 3 0 0 0 0
29 3.044
47.309 0 0ub.04 247. 570 0 0 0 0 0 2 4 0 0 0 0
162 .788
51 4.4 26 1 0Mar.04 622 .20 4 0 1 0 0 0 25 0 0 0 0
32 .532
1 .43 8 .949 0 0Nis.04 429 .33 1 0 0 0 0 0 2 6 1 0 0 0
23.468
101 .846 0 0May.04 453.15 6 0 0 1 0 0 2 7 0 0 0 0
4.50 3.4 56
754 0 0
az. 04 320 .10 3 0 0 0 0 0 28 0 1 0 0
500 .90 4
62 .21 3 0 0Tem.04 451 .77 9 0 0 0 1 0 29 0 0 0 0
0
1 .600 .939 0 0A
u.04 249 .482 0 0 0 0 0 30 0 0 0 0
0
85 4.90 4 0 1Eyl.04 744. 58 3 0 0 0 0 1 31 0 0 0 0
46. 10 4
1 .51 4.7 07 0 0Eki.04 421 .18 6 0 0 0 0 0 32 0 0 1 0
92 .252
384.989 0 0Kas.04 397.367 0 0 0 0 0 33 0 0 0 1
4.869 .952
28 .512 0 0Ara.04 269 .09 6 0 0 0 0 0 34 0 0 0 0
376.55 6
176.73 1 0 0
SIGNIFICANTREGRESSIONMODEL PARAMETERS INSIGNIFICANT PARAMETERS
SUMMAR
OUTPUT
Reg r e i on St a ti ti
Mu ltip le R 0,80R Squa re 0 ,64
Adjus te d R Squa re 0 ,58
Standa rd Error 81 .743 ,63
Obs erv a tio ns 34 ,00
ANOVA
d f SS S F Si g n i f i a n e F
Regre ss io n 5,00 335 .703 .829 .762 ,64 67 .140 .765 .952 ,53 10 ,05 0 ,00
Re sidua l 28 ,00 187 .096 .586 .658 ,80 6 .682 .020 .952 ,10
To ta l 33 ,00 522 .800 .416 .421 ,44
C oe ff i i en t St a n da r d Err o r t St a t P-v a l u e Lowe r 95 %
e r 95% Lowe r 95,0 %
er 95,0 %
In terce p t 315 .324 ,40 18 .278 ,43 17 ,25 0 ,00 277 .882 ,73 352 .766 ,07 277 .882 ,73 352 .766 ,07
Jan_D 240 .117 ,60 60 .622 ,70 3 ,96 0 ,00 115 .937 ,63 364 .297 ,57 115 .937 ,63 364 .297 ,57
Ma r _D 143 .536 ,27 50 .610 ,68 2 ,84 0 ,01 39 .864 ,98 247 .207 ,55 39 .864 ,98 247 .207 ,55
May_D 159 .932 ,27 50 .610 ,68 3 ,16 0 ,00 56 .260 ,98 263 .603 ,55 56 .260 ,98 263 .603 ,55
Ju l _D 130 .725 ,93 50 .610 ,68 2 ,58 0 ,02 27 .054 ,65 234 .397 ,22 27 .054 ,65 234 .397 ,22
Se p_D 278 .109 ,60 50 .610 ,68 5 ,50 0 ,00 174 .438 ,31 381 .780 ,89 174 .438 ,31 381 .780 ,89