7/25/2019 Main Output

1/5

Sales & price

Model Summary

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .859a .738 .729 268.398

a. Preditors! "#o$sta$t%& 'rie

Interpretation: R Square .738 means 74% independent variables can be explained by R Scquare.Rest

26% can explain frm t!er surces

ANOVAa

Model Sum of Squares df Mea$ Square ( Si).

1

Re)ressio$ 569262*.+15 1 569262*.+15 79.+23 .+++,

Residual 2+17+*2.652 28 72+37.238

-otal 77+9666.667 29

a. e'e$de$t /aria,le! sales 0olume

,. Preditors! "#o$sta$t%& 'rie

Interpretation: Si"nificance value is .##. $t is less t!an .#. S t!ere is relatins!ip exist bet&een price

' sales vlume. (!ere is ne"ative relatin. $f price increase sales decrease ' if price decrease sales

increase

Coefficients

Model $sta$dardied #oeffiie$ts Sta$dardied

#oeffiie$ts

t Si).

Std. Error eta

1"#o$sta$t% 2518.6+8 172.681 1*.585 .+++

'rie 41.931 .217 4.859 48.89+ .+++

a. e'e$de$t /aria,le! sales 0olume

Interpretation: ) unit c!an"e in t!e independent variable *price+ indicates)72 amunt f c!an"e in t!e

dependent variable is. (!ere is psitive relatins!ip.

1

7/25/2019 Main Output

2/5

Sales & discount

Model Summary

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .859a .738 .729 268.398

2 .859, .738 .719 273.316

a. Preditors! "#o$sta$t%& 'rie

,. Preditors! "#o$sta$t%& 'rie& amou$t of disou$t

Interpretation: R Square .738 means 74% independent variables ' dependent variables can be

explained by R Scquare.Rest 26% can explain frm t!er surces. (!ere is strn" relatins!ip bet&een

dependent ' independent variable

ANOVAa

Model Sum of Squares df Mea$ Square ( Si).

1

Re)ressio$ 569262*.+15 1 569262*.+15 79.+23 .+++,

Residual 2+17+*2.652 28 72+37.238

-otal 77+9666.667 29

2

Re)ressio$ 569272*.932 2 28*6362.*66 38.1+3 .+++

Residual 2+169*1.735 27 7*7+1.5*6

-otal 77+9666.667 29

a. e'e$de$t /aria,le! sales 0olume

,. Preditors! "#o$sta$t%& 'rie

. Preditors! "#o$sta$t%& 'rie& amou$t of disou$t

Interpretation: Si"nificance value is .##. $t is less t!an .#. S t!ere is relatins!ip exist bet&een price

discunt ' sales vlume. (!ere is psitive relatin. $f discunt increase sales als increase

Coefficients

Model $sta$dardied #oeffiie$ts Sta$dardied

#oeffiie$ts

t Si).

Std. Error eta

1"#o$sta$t% 2518.6+8 172.681 1*.585 .+++

'rie 41.931 .217 4.859 48.89+ .+++

2

"#o$sta$t% 25+3.*53 **8.275 5.585 .+++

'rie 41.922 .32* 4.855 45.933 .+++

amou$t of disou$t 1.9+8 51.91* .++5 .+37 .971

a. e'e$de$t /aria,le! sales 0olume

2

7/25/2019 Main Output

3/5

Interpretation: ) unit c!an"e in t!e independent variable *discunt+ indicates )72 amunt f c!an"e in

t!e dependent variable. (!ere is psitive relatins!ip.

Sales & advertisementModel Summary

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .859a .738 .729 268.398

2 .935, .87* .865 189.52+

a. Preditors! "#o$sta$t%& 'rie

,. Preditors! "#o$sta$t%& 'rie& ad0ertiseme$t

Interpretation: R Square .738 ' .874 mean 74% independent variables ' 87% #f dependent variables

can be explained by R Scquare.Rest f data can be explained frm t!er surces (!ere is very strn"

relatins!ip bet&een dependent ' independent variable

ANOVAa

Model Sum of Squares df Mea$ Square ( Si).

1

Re)ressio$ 569262*.+15 1 569262*.+15 79.+23 .+++,

Residual 2+17+*2.652 28 72+37.238

-otal 77+9666.667 29

2

Re)ressio$ 6739885.857 2 33699*2.929 93.82* .+++

Residual 96978+.8+9 27 35917.8+8

-otal 77+9666.667 29

a. e'e$de$t /aria,le! sales 0olume

,. Preditors! "#o$sta$t%& 'rie

. Preditors! "#o$sta$t%& 'rie& ad0ertiseme$t

Interpretation: Si"nificance value is .##. $t is less t!an .#. S t!ere is relatins!ip exist bet&een sales

vlume ' advertisement. (!ere is psitive relatin. $f advertisement increase sales increase

3

7/25/2019 Main Output

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Coefficients

Model $sta$dardied #oeffiie$ts Sta$dardied

#oeffiie$ts

t Si).

Std. Error eta

1"#o$sta$t% 2518.6+8 172.681 1*.585 .+++

'rie 41.931 .217 4.859 48.89+ .+++

2

"#o$sta$t% 4151+.788 756.117 41.998 .+56

'rie 1.++2 .56* .**6 1.776 .+87

ad0ertiseme$t 3.+1* .558 1.356 5.*++ .+++

a. e'e$de$t /aria,le! sales 0olume

Interpretation: ) unit c!an"e in t!e independent variable *advertisement+ indicates )72 amunt f

c!an"e in t!e dependent variable is. (!ere is psitive relatins!ip.

Sales & outlet

Model Summary

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .859a .738 .729 268.398

2 .9*2, .888 .88+ 178.836

a. Preditors! "#o$sta$t%& 'rie

,. Preditors! "#o$sta$t%& 'rie& $um,er of outlet

Interpretation: R Square .738 ' .888 mean 74% independent variables ' 8,% dependent variables

can be explained by R Scquare.Rest f data can be explained frm t!er surces (!ere is very strn"

relatins!ip bet&een dependent ' independent variable.

ANOVAa

Model Sum of Squares df Mea$ Square ( Si).

1

Re)ressio$ 569262*.+15 1 569262*.+15 79.+23 .+++,

Residual 2+17+*2.652 28 72+37.238

-otal 77+9666.667 29

2

Re)ressio$ 68*61*+.9+5 2 3*23+7+.*52 1+7.+3+ .+++

Residual 863525.762 27 31982.*36

-otal 77+9666.667 29

4

7/25/2019 Main Output

5/5

a. e'e$de$t /aria,le! sales 0olume

,. Preditors! "#o$sta$t%& 'rie

. Preditors! "#o$sta$t%& 'rie& $um,er of outlet

Interpretation: Si"nificance value is .##. $t is less t!an .#. S t!ere is relatins!ip exist bet&een sales

vlume ' number f utlet. (!ere is psitive relatin. $f number f utlet increase sales increase

Coefficients

Model $sta$dardied #oeffiie$ts Sta$dardied

#oeffiie$ts

t Si).

Std. Error eta

1"#o$sta$t% 2518.6+8 172.681 1*.585 .+++

'rie 41.931 .217 4.859 48.89+ .+++

2

"#o$sta$t% 4769.*97 559.*66 41.375 .18+

'rie .5+7 .*31 .226 1.177 .2*9

$um,er of outlet 25.15+ *.188 1.152 6.++6 .+++

a. e'e$de$t /aria,le! sales 0olume

,.

Interpretation: ) unit c!an"e in t!e independent variable *discunt+ indicates )72 amunt f c!an"e in

t!e dependent variable. (!ere is psitive relatins!ip.

5