How to solve assignments

Shalvin Kumar Kumar Saha

13EE10045

5. Seasonal Variation Seasonal variation is the variation that is seen only in a particular season or a particular period of time. For example consider sales of !Sculpture of "ord #anesha$ %e can clearly see that sales of such item %ill soar %hen dates are close to #anesha &haturthi. Similarly sales of %oollen apparels %ill 'o hi'h in the %inter season and sales of cotton out(ts %ill soar in summer. summer. )ummy Varia*le +echni,ue So in the )ummy Varia*le +echni,ue +echni,ue %e declare fe% varia*le and assi'n them some values in order to conduct re'ression on such data to forecast future values. E,uation -  / a 1  *1  d1  *2  d2  *3  d3  d1 d2 d3. are dummy varia*les and have values either 0 or 1 %hich depends on if you are usin' * 1 *2 *3.. respectively. So this is the model e,uation that %e %ill use and predict future values. 6o%ever this a re'ression techni,ue and values of co7e8cient co7 e8cient chan'e accordin'ly after every analysis.

6. #iven 9:tec depends on ;ar?@ ?- ?ro(t. f>x@ is a function such that it increases i ncreases over the positive x axis. At could *e ) / a?*B ?7C ?ro(tB a and * are some constants such that a is 'reater than 0.

4. E,uation Q = 70 – 3.5P – 0.6M + 4P Z

D- )emand ?- ?rice

;- Ancome ?:- ?rice of related 'ood  o% since %ith increase in ; >income@ the demand decreases it is an inferior  product. ?rice of : increases / )emand of D increases /C +hey are substitute for each other. ?/10. ; /30. ?: / G. D / H0 I 3.510 I 0.G30  4G / H0 I 35 I 1J  24 / 35  G / 41 9ssume )emand / D / ). ?rice Elasticity- >ΔD/D)/ (ΔP/P) / >)L?@>?L)@ / 73.5>10L41@ / 70.J53 Ancome Elasticity Elasticity-- >ΔD/D)/ (ΔM/M) / >)L;@>;L)@ / 70.G>30L41@ / 70.43M0 &ross7?rice Elasticity Elasticity-- >ΔD/D)/ (ΔPz/Pz) / >)L?:@>?:L)@ / 4>GL41@ / 0.5J5

2. 12 in ?arenthesis means the sales in the (rst year in the consideration. 12 means 12000 laas per the detail in the ,uestion. Sales Fi'ure ear   ear 1MM1 1MM2 1MM3 1MM4 1MM5 1MMG 1MMH 1MMJ 1MMM 2000 2001 2002 2003 2004 2005 200G 200H

Sales 12 13.0J 14.25 H2 15.54 035 1G.M3 JMJ 1J.4G 34M 20.12 52 21.M3 G4H 23.M1 0H5 2G.0G 2H2 2J.40 J3G 30.MG 512 33.H5 1MJ 3G.HJ MGG

t 0 1 2 3 4 5 G H J M 10 11 12 13 14 15 1G

40.10 0H2 43.H0 MHM 4H.G4 3GH

1. >a@ Nsin' S;973 the result is  ello%  ello% indicates predicted value.

;ont h 1 2 3 4 5 G H J M

Sales S;973 2M 23 22 24.GGG 20 GH 21.GGG 1J GH 1G 20 1J 1J 1H.333 1H.333 33 33 1H.111 1H.111 11 11

>*@ O;9 I Oei'hted ;ean 9vera'e ;onth O;9 1 2 3 4 25.J 5 22.1 G 20.G

>c@ Exponential Smoothin' for Puly>month / H@ %ith a / 0.1 Foreca ;onth Sales st 1 2M 2M

2 3 4 5

23 22 20 1J

G

1G

H

2M 2J.4 2H.HG 2G.MJ4 2G.0J5 G 25.0HH 04

3. R 2 0.2247

Dependent variable: S $b%ervati"n%: 36 (ariable (ariable nter,ept  R a / 1H50JG.0 * / 0.J550 c / 70.2J4

Para)eter *%ti)ate '750&6.0 0.&550 ! 0.2&4

!rati" 4.7&' Standard err"r  63&2'.0 0.3250 0.'64

p!val#e "n  0.0'50 t!rati" 2.74 2.63 ! '.73

p!val#e 0.00-& 0.0'2& 0.0-27

p value for 9 >i.e. Van'uard Van'uard expenditure@ is 0.012J %hich is less than 0.0150>common alpha level@ and therefore it has an eQect on the sales of the Rri'ht Side )eter'ent.

p value for  >i.e. competitors expenditure@ is 0.0M2H %hich is 'reater than 0.015>common alpha level@ and thus doesnt (t %ith the hypothesis that it aQects the sales of Rri'ht Side )eter'ent.

Expected sales- '750&6.0

= '&20&6 a ee1.

+ 0.&&50/401+!0.2&4/'001 0.&&50/401+!0.2&4/'001