spss prject final

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 Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent meanofimb 50 98.0% 1 2.0% 51 100.0% meanofinf 50 98.0% 1 2.0% 51 100.0% meanofadv 50 98.0% 1 2.0% 51 100.0% meanofper 50 98.0% 1 2.0% 51 100.0%  Now we check the normality of data. Tests of Normality Kolmogorov-Smirnov a  Shapiro-Wilk Statistic df Sig. Statistic df Sig. meanofimb .147 50 .009 .961 50 .100 meanofinf .108 50 .198 .939 50 .012 meanofadv .140 50 .016 .964 50 .125 meanofper .254 50 .000 .787 50 .000 a. Lilliefors Significance Correction with the help of Kolmogorov we come to know that mean of influence of window display is normal because the significance level is greater than 0.05 and other variables is not normal because there significance level is not greater than 0.05. By using QQ plot and Histogram I only check the mean of influence so that I come to know that is normal or not.

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Page 1: Spss Prject Final

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Case Processing Summary 

Cases

Valid Missing Total

N Percent N Percent N Percent

meanofimb 50 98.0% 1 2.0% 51 100.0%

meanofinf 50 98.0% 1 2.0% 51 100.0%

meanofadv 50 98.0% 1 2.0% 51 100.0%

meanofper 50 98.0% 1 2.0% 51 100.0%

 Now we check the normality of data.

Tests of Normality 

Kolmogorov-Smirnova  Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

meanofimb .147 50 .009 .961 50 .100

meanofinf .108 50 .198 .939 50 .012

meanofadv .140 50 .016 .964 50 .125

meanofper .254 50 .000 .787 50 .000

a. Lilliefors Significance Correction

with the help of Kolmogorov we come to know that mean of influence of window display is

normal because the significance level is greater than 0.05 and other variables is not

normal because there significance level is not greater than 0.05.

By using QQ plot and Histogram I only check the mean of influence so that I come to know that

is normal or not.

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By seen Q-Q Plot and Histogram I come to know that data is normal

 Now apply parametric test on normally variance data.

Group Statistics 

gender N Mean Std. Deviation Std. Error Mean

meanofinf male 27 2.3704 .48719 .09376

female 23 2.1739 .50809 .10594

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Independent Samples Test

Levene's Test forEquality of Variances t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed)

Mean

Difference

Std. Error

Differencemeanofinf Equal

variancesassumed

.015 .903 1.393 48 .170 .19646 .14099

Equalvariancesnotassumed

1.389 46.053 .172 .19646 .14147

From the levene’s test for equality of variance the significance level of mean of influence of window

display us 0.903 which is greater than 0.05 which shows that the variance mean of influence of window

display are equal.

From t test for equality of mean the significance level of influence of window display is 0.170 which is

greater than 0.05 so we accept H0 that is µ1=µ2 which shows that male and female are equally influence

on influence of window display.

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Mann-Whitney Test

Ranks 

gender N Mean Rank Sum of Ranks

meanofimb male 27 25.54 689.50

female 23 25.46 585.50

Total 50

meanofadv male 27 24.44 660.00

female 23 26.74 615.00

Total 50

meanofper male 27 27.91 753.50

female 23 22.67 521.50

Total 50

Test Statisticsa 

meanofimb meanofadv meanofper

Mann-Whitney U 309.500 282.000 245.500

Wilcoxon W 585.500 660.000 521.500

Z -.020 -.564 -1.270

 Asymp. Sig. (2-tailed) .984 .573 .204

a. Grouping Variable: gender

Mean of impulse buying, advertisement and sales promotion and personal experience have

significance value 0.984, 0.573 and 0.204 respectively which are all less than 0.05 it mean we

accept H0 for all the 3 variables which shows that male and female both like impulse buying

 behavior both male and female are attracted by advertisement and sale promotion and similarly

the personal experience of both male female are same.