Regression for Sale Unit of Men’s Wallet

Group Assignment:

Regression for Sale Unit of Men’s Wallet

Group A

Ai Huanhuan 14210690645

Chen Lijuan 15210690175

Gao Yuyang 15210690240

Hong Sha 15210690278

Li Yishan 15210690374

Wang Dan 15210690510

Kyungrok Kim 15210690747

Kim Bokyung 15210690767

Background and Introduction

Nowadays E-commerce is becoming more and more popular and increasing number of shops selling clothes and accessories are being opened on Taobao, Tmall, etc. But online shoppers have to consider many factors to maximize their sales and profit and at the same time reduce the risks. So we tried to find the relationships between the sales volume of Men’s Wallets and some factors including operation time, shop region, comment numbers, customer numbers, product prices, discount percentages, etc. These thousands of data were collected from the back operation system of Taobao and Tmall. After analysis, we shall give a regression model, in other words, a formula, to give a guidance or reference to online shoppers or potential online shoppers to operate their Men’s Wallet online shops.

Data

We collected a package of data about sales of men’s wallets. The raw data are from online shopping platforms-Taobao, Tmall and JD worldwide. Of course, they are also from different online stores. The sample size is 1790. We selected 8 dimensions of data which are both what we are interested in and quantifiable. Then we sort out the data as follows.

We denote 1 dependent variable and 7 independent variables. Here are details.

Y-Sales Volume (unit), means how many wallets are sold in the store during the operation time;

X1-Operation time (day), means how many days from the day the store started to Dec 1st,2015;

X2-Region, logical value, means whether the store provides free shopping, if yes, the number is 1, if not, 0;

X3-Price, means original price;

X4-Discount, means currently promoted price ratio of original price;

X5-Customers, means the number of customers who bought the wallets;

X6-Comments, means the number of comments the store got;

X7-Collection Add, means how many accounts added the store on their collection.

Understand the data: mean, variance, histogram

For the raw data, we have 7 variables for reference about the sale units of the men’s wallet.

We will calculate mean, variance and generate histogram to understand the data Preliminary. Correlation has been shown and Scatter plot can be found in check part. So here we will show mean, variance and histogram.

Due there’s a logic number (0, 1), it’s no use to calculate the mean and variance of this kind of data. So we will not calculate the region mean, variance and hitogram.

• Sales Volume (Unit)

Mean: 177

Variance: 232161

[pic 1]

• Operation Time (Day)

Mean: 896

Variance: 509659

[pic 2]

• Price (RMB)

Mean: 328.8

Variance: 186758.5

[pic 3]

• Discount (%)

Mean: 32.48%

Variance: 0.063

[pic 4]

• Customers (People)

Mean: 109

Variance: 85984

[pic 5]

• Comments (Item)

Mean: 258

Variance: 1161080

[pic 6]

• Collection Add (Item)

Mean: 712

Variance: 4353023

[pic 7]

Then we got the correlations of the variables through computer: