The aim of this project is enable category managers of Walmart to check the weekly and monthly sales of the departments. Analysis includes the effect of markdowns on the sales and the extent of effect on the sales by fuel prices, temperature, unemployment, CPI etc. Has been analyzed using simple and multiple linear regression models.
The decision makers of Walmart should be able to analyze the effect of various factors affecting the sales of the products in their stores.
In this problem we have analyzed sales across different departments by store type and created weekly and monthly. We have analyzed the effect of various factors such as temperature, store size, fuel prices, markdown in prices, unemployment and CPI to determine Which factors have a statistical significance in explaining sales in the stores by using simple and multiple linear regression
In this project we focused retail analysis with Walmart data and answer the following questions:
-
Which stores have maximum and sales?
-
Which store has maximum standard deviation i.e., the sales vary a lot?. Also, find out the coefficient of mean to standard deviation.
-
Which store/s has good quarterly growth rate in Q3’2012?
-
Find out holidays which have higher sales than the mean sales in non-holiday season for all stores together.
-
Provide a monthly and semester view of sales in units and give insights.