Sheet1

SAVE OUTFILE='C:\Users\Saleem\Documents\Deepanshu.sav' /COMPRESSED.DESCRIPTIVES VARIABLES=Gender Age DrivingInsideStore NoticeFeatureInStore /STATISTICS=MEAN STDDEV MIN MAX.

DescriptivesNotesOutput Created15-APR-2015 18:48:10CommentsInputDataC:\Users\Saleem\Documents\Deepanshu.savActive DatasetDataSet0FilterWeightSplit FileN of Rows in Working Data File100Missing Value HandlingDefinition of MissingUser defined missing values are treated as missing.Cases UsedAll non-missing data are used.SyntaxDESCRIPTIVES VARIABLES=Gender Age DrivingInsideStore NoticeFeatureInStore /STATISTICS=MEAN STDDEV MIN MAX.ResourcesProcessor Time00:00:00.03Elapsed Time00:00:00.25

[DataSet0] C:\Users\Saleem\Documents\Deepanshu.savDescriptive StatisticsNMinimumMaximumMeanStd. DeviationGender1001.002.001.4300.49757Age1001.004.001.4900.71767DrivingInsideStore1001.006.003.39001.52352NoticeFeatureInStore1001.004.002.35001.13150Valid N (listwise)100DATASET ACTIVATE DataSet0.

SAVE OUTFILE='C:\Users\Saleem\Documents\Deepanshu.sav' /COMPRESSED.FREQUENCIES VARIABLES=Gender Age DrivingInsideStore NoticeFeatureInStore /PIECHART PERCENT /ORDER=ANALYSIS.

FrequenciesNotesOutput Created15-APR-2015 18:51:26CommentsInputDataC:\Users\Saleem\Documents\Deepanshu.savActive DatasetDataSet0FilterWeightSplit FileN of Rows in Working Data File100Missing Value HandlingDefinition of MissingUser-defined missing values are treated as missing.Cases UsedStatistics are based on all cases with valid data.SyntaxFREQUENCIES VARIABLES=Gender Age DrivingInsideStore NoticeFeatureInStore /PIECHART PERCENT /ORDER=ANALYSIS.ResourcesProcessor Time00:00:03.61Elapsed Time00:00:04.44

[DataSet0] C:\Users\Saleem\Documents\Deepanshu.savStatisticsGenderAgeDrivingInsideStoreNoticeFeatureInStoreNValid100100100100Missing0000

Frequency TableGenderFrequencyPercentValid PercentCumulative PercentValidMale5757.057.057.0Female4343.043.0100.0Total100100.0100.0AgeFrequencyPercentValid PercentCumulative PercentValid16-256262.062.062.026-352929.029.091.036-4577.07.098.046-5522.02.0100.0Total100100.0100.0DrivingInsideStoreFrequencyPercentValid PercentCumulative PercentValidStore Exterior Graphics and Signage1313.013.013.0Window Display Setting1818.018.031.0Outer Glimpse of Store2323.023.054.0Kind of Merchandise on display1818.018.072.0Brand Name and Logo1919.019.091.0Promotional Offering at the entrance ( Sale / Discounts)99.09.0100.0Total100100.0100.0NoticeFeatureInStoreFrequencyPercentValid PercentCumulative PercentValidbold Graphics3030.030.030.0Music and Lightning2727.027.057.0Mannequin Styling2121.021.078.0Creative product Display2222.022.0100.0Total100100.0100.0

Pie Chart

CROSSTABS /TABLES=Gender BY Age BY DrivingInsideStore /FORMAT=AVALUE TABLES /CELLS=COUNT /COUNT ROUND CELL.

CrosstabsNotesOutput Created15-APR-2015 18:53:01CommentsInputDataC:\Users\Saleem\Documents\Deepanshu.savActive DatasetDataSet0FilterWeightSplit FileN of Rows in Working Data File100Missing Value HandlingDefinition of MissingUser-defined missing values are treated as missing.Cases UsedStatistics for each table are based on all the cases with valid data in the specified range(s) for all variables in each table.SyntaxCROSSTABS /TABLES=Gender BY Age BY DrivingInsideStore /FORMAT=AVALUE TABLES /CELLS=COUNT /COUNT ROUND CELL.ResourcesProcessor Time00:00:00.02Elapsed Time00:00:00.01Dimensions Requested3Cells Available142964

[DataSet0] C:\Users\Saleem\Documents\Deepanshu.savCase Processing SummaryCasesValidMissingTotalNPercentNPercentNPercentGender * Age * DrivingInsideStore100100.0%00.0%100100.0%Gender * Age * DrivingInsideStore CrosstabulationCountDrivingInsideStoreAgeTotal16-2526-3536-4546-55Store Exterior Graphics and SignageGenderMale53109Female21014Total741113Window Display SettingGenderMale10212Female606Total16218Outer Glimpse of StoreGenderMale5319Female112114Total165223Kind of Merchandise on displayGenderMale4509Female4329Total88218Brand Name and LogoGenderMale831113Female23106Total1062119Promotional Offering at the entrance ( Sale / Discounts)GenderMale325Female224Total549TotalGenderMale35183157Female27114143Total622972100COMPUTE ImpulseBuying=MEAN(MerchandiseandMannequinIMP,pricetalkerspromoteimpulsebuying).EXECUTE.CORRELATIONS /VARIABLES=Gender ImpulseBuying /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE.

CorrelationsNotesOutput Created15-APR-2015 18:57:02CommentsInputDataC:\Users\Saleem\Documents\Deepanshu.savActive DatasetDataSet0FilterWeightSplit FileN of Rows in Working Data File100Missing Value HandlingDefinition of MissingUser-defined missing values are treated as missing.Cases UsedStatistics for each pair of variables are based on all the cases with valid data for that pair.SyntaxCORRELATIONS /VARIABLES=Gender ImpulseBuying /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE.ResourcesProcessor Time00:00:00.03Elapsed Time00:00:00.14

[DataSet0] C:\Users\Saleem\Documents\Deepanshu.savCorrelationsGenderImpulseBuyingGenderPearson Correlation1.205*Sig. (2-tailed).041N100100ImpulseBuyingPearson Correlation.205*1Sig. (2-tailed).041N100100*. Correlation is significant at the 0.05 level (2-tailed).CROSSTABS /TABLES=Gender BY Age BY NoticeFeatureInStore /FORMAT=AVALUE TABLES /CELLS=COUNT /COUNT ROUND CELL.

CrosstabsNotesOutput Created15-APR-2015 18:58:04CommentsInputDataC:\Users\Saleem\Documents\Deepanshu.savActive DatasetDataSet0FilterWeightSplit FileN of Rows in Working Data File100Missing Value HandlingDefinition of MissingUser-defined missing values are treated as missing.Cases UsedStatistics for each table are based on all the cases with valid data in the specified range(s) for all variables in each table.SyntaxCROSSTABS /TABLES=Gender BY Age BY NoticeFeatureInStore /FORMAT=AVALUE TABLES /CELLS=COUNT /COUNT ROUND CELL.ResourcesProcessor Time00:00:00.02Elapsed Time00:00:00.02Dimensions Requested3Cells Available142964

[DataSet0] C:\Users\Saleem\Documents\Deepanshu.savCase Processing SummaryCasesValidMissingTotalNPercentNPercentNPercentGender * Age * NoticeFeatureInStore100100.0%00.0%100100.0%Gender * Age * NoticeFeatureInStore CrosstabulationCountNoticeFeatureInStoreAgeTotal16-2526-3536-4546-55bold GraphicsGenderMale95115Female113115Total208230Music and LightningGenderMale97218Female5319Total1410327Mannequin StylingGenderMale73010Female73111Total146121Creative product DisplayGenderMale1030114Female42118Total1451222TotalGenderMale35183157Female27114143Total622972100DESCRIPTIVES VARIABLES=improvedinthestores /STATISTICS=MEAN STDDEV MIN MAX.

DescriptivesNotesOutput Created15-APR-2015 18:59:08CommentsInputDataC:\Users\Saleem\Documents\Deepanshu.savActive DatasetDataSet0FilterWeightSplit FileN of Rows in Working Data File100Missing Value HandlingDefinition of MissingUser defined missing values are treated as missing.Cases UsedAll non-missing data are used.SyntaxDESCRIPTIVES VARIABLES=improvedinthestores /STATISTICS=MEAN STDDEV MIN MAX.ResourcesProcessor Time00:00:00.00Elapsed Time00:00:00.01

[DataSet0] C:\Users\Saleem\Documents\Deepanshu.savDescriptive StatisticsNMinimumMaximumMeanStd. Deviationimprovedinthestores1001.005.002.55001.35866Valid N (listwise)100COMPUTE VisualMerchandizing=MEAN(AttractiveMannequinandWindowdisplay,goodlayoutMovingbrowsingspaceAmbience,ExteriorStoreSignageandgraphic,Promotionalofferingsatstoreentrance,storelightingandmusic,Pricetalkersmerchandiseandmannequindisplayedattheentrancewindow).EXECUTE.CORRELATIONS /VARIABLES=VisualMerchandizing storecommunicationelementspurchasedecision /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE.

CorrelationsNotesOutput Created15-APR-2015 19:02:59CommentsInputDataC:\Users\Saleem\Documents\Deepanshu.savActive DatasetDataSet0FilterWeightSplit FileN of Rows in Working Data File100Missing Value HandlingDefinition of MissingUser-defined missing values are treated as missing.Cases UsedStatistics for each pair of variables are based on all the cases with valid data for that pair.SyntaxCORRELATIONS /VARIABLES=VisualMerchandizing storecommunicationelementspurchasedecision /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE.ResourcesProcessor Time00:00:00.03Elapsed Time00:00:00.07

[DataSet0] C:\Users\Saleem\Documents\Deepanshu.savCorrelationsVisualMerchandizingstorecommunicationelementspurchasedecisionVisualMerchandizingPearson Correlation1.420**Sig. (2-tailed).000N100100storecommunicationelementspurchasedecisionPearson Correlation.420**1Sig. (2-tailed).000N100100**. Correlation is significant at the 0.01 level (2-tailed).