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INTERPRETATION OF FACTORANALYSIS

1. KMO and Bartlett’s Test

KMO basically measures sampling adequacy i.e. appropriateness of factor

analysis. It’s value should be greater than .0 to proceed since in this case the value

of KMO is!

KMO " 0.#$% & .0

Thus' (actor analysis is appropriate and )e can proceed further.

Bartlett’s test indicates the strength of relationship among variables. It tests the null

hypothesis that the variables are uncorrelated. *ince in this case'

*ignificant value " 0.000+appro,- 0.0

Thus it is statistically significant/ i.e. the null hypothesis can be reected and there

is a correlation bet)een them.

 The variables are as follows:

V1: Maggi is he !rs bra"# ha $o%es o &o'r %i"# whe" &o'

hi"( abo' "oo#les)

V*: Maggi "oo#les is goo# for healh)

V+: we will ,refer si%ilar ,ro#'$s of oher bra"#s raher ha"

%aggi)

V-: Maggi "oo#les is ,re.ere# o"l& b& $hil#re"s)

V/: Maggi is ,er$eive# as a 0'"( foo#)

V: Tase

V2: 3ra"# i%age

V14 : Pri$e

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V11: healh i"gri#e"s

V1*: Varie&

1. 2ommunalities

It sho)s ho) much of the variance in a variable has been accounted for by the

e,tracted factors thus' it sho)s the percentage of variances in a variable that is

captured by the common underlying factor. In this case' the value is highest for

variable 3+ highest value 0.3$4- i.e 3$.45 of variance is captured by underlying

factor and is lo)est for variable 60 +lo)est value 0.%70- i.e. %75 is captured by

factor.

$. Total 8ariance 9,plained

9igen values represents the percentage of total variance e,plained by each factor.

Its value should be greater than 6.Thus in this case only %factors have been found

)hose eigen values greater than 6.These factors cumulatively e,plained #3.#075.

*o' around $65 variation )e are not able to capture it' but still )e are able to

deduct factors from 60 to %.

%. 2omponent matri,

It sho)s loading of the 60 variables on the % factor e,tracted. The higher the

absolute value of loading the more the factor contribute to variable. In the

component matri, the factor )hose absolute value is greater than 0.0 that factor

)ill be loaded on the variables subsequently. (rom the table )e found out that the

variable 6 is loaded on factor 6.81 is loaded on factor %. 8% is loaded on factor

$.8 is loaded on factor $. 8# is loaded on factor 1. 83 is loaded on factor 6.87 isloaded on factor 6. 860 is loaded on factor 6. 861 is loaded on factor 1.

:s 83 is loaded on factor 6 ; 1 both' so )e have to find out from rotated

comparison matri, the final findings.

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In Rotated comparison matrix, )e have find out that the variable 6 is loaded on

factor6' 81 is loaded on factor %' 8% is loaded on factor $' 8 is loaded on factor

%' 8# is loaded on factor 6' 83 is loaded on factor 6' 87 is loaded on factor $' 860

is loaded on factor 1' 866 is loaded on factor 1' 861 is loaded on factor 1.

(actor 6! 0.$4#v6<.67%v1= 0.60v%= 0.61$v= 0.%3v#= 0.1#%v3= 0.0$v7<

0.011v60<0.064v66<0.061v61

(actor 1! <0.0%v6= 0.017v1= 0.6$#v%< 0.64#v<0.06%v#=0.03%v3<

0.0$1v7=0.17v60 =0.%1%v66= 0.64v61

(actor $! 0.01%v6=0.077v1<0.$v%<0.6$v<0.11#v#=0.1%v3=0.%$v7 =0.64%v60

 > 0.0#6v66< 0.1#v61

(actor %! <0.004v6=0.#%7v1= 0.646v%= 0.%%v<0.6#$v#<0.006v3= 0.16$v7<0.0#$v60=0.0$%v66<0.646v61

Conclusion:

Variables Factors Name

  86'v#'v3 6 ?ecognition

 860'v66'v61 1

 8%'v7 $ brand loyalty

81'v %

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