SAS Data Analysis on Retail Clothing Data Set
SAS program to evaluate a clothing sales file, including statistical mean data, univariate anaysis and correlationship analysis. Data file to be used with the SAS program is Cloting_Store_Data.csv - a comma deliminated data file.
Variables:
The following variables contain the percent of total sales spent by the customer on the respective product category:
• PSWEATERS: Sweaters
• PKNIT_TOPS: Knit tops
• PKNIT_DRES: Knit dresses
• PBLOUSES: Blouses
• PJACKETS: Jackets
• PCAR_PNTS: Career pants
• PCAS_PNTS: Casual pants
• PSHIRTS: Shirts
• PDRESSES: Dresses
• PSUITS: Suits
• POUTERWEAR: Outerwear
• PJEWELRY: Jewelry
• PFASHION: Fashionable wear
• PLEGWEAR: Leg wear
• PCOLLSPEND: Collectibles
• GMP: Gross margin percentage
• PROMOS: Number of marketing promotions on file
• DAYS: Number of days the customer has been on file
• MARKDOWN: Markdown percentage on customer purchases
• CLUSTYPE: MICROVISION LIFESTYLE CLUSTER TYPE
• PERCRET: Percent of Returns
• In days between purchase: Number of days between purchases
• In lifetime avg time betw visits: Lifetime average time between visits.
Six most common lifestyle cluster types in the dataset:
1. Cluster 10 Home Sweet Home: families, medium-high income and education, manager/professionals, technical/sales
2. Cluster 1 Upper Crust: metropolitan families, very high income and education, homeowners, managers/professionals
3. Cluster 4 Mid-life Success: families, very high education, high income, managers/professionals, technical/ sales
4. Cluster 16 Country Home Families: large families, rural areas, medium education, medium income, precision/crafts
5. Cluster 8 Movers and Shakers: singles, couples, students and recent graduates, high education and income, managers/professionals, technical/sales
6. Cluster 15 Great Beginnings: young, singles and couples, medium-high education, medium income, some renters, managers/professionals, technical/sales