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Our aim was to find the relationship between number of purchases on Black Friday sales and variables such as occupation, marital status, age groups, gender, city category and number of years lived in a city. Another objective was to establish a market basket of items from product category A, B and C.

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Black Friday Sales

Description

Our aim was to find the relationship between number of purchases on Black Friday sales and variables such as occupation, marital status, age groups, gender, city category and number of years lived in a city. Another objective was to establish a market basket of items from product category A, B and C.

Getting Started

The analysis is divided into two parts:

  1. Exploratory analysis
  2. Linear Regression

Exploratory analysis is used to analyze the purchase behaviour of consumers based on amount spent, gender, age group, occupation, etc.

Linear Regression is used in order to understand which attribute is more important than others so that in the future the offers are made according to the weightage of the attribute.

Dependencies

  • RStudio

Authors

  • Karan
  • Gunnika
  • Ravinder
  • Amit
  • Sparsh

Dataset

Please read the report to better understand how different attributes like consumer's age, gender, occupation affects the purhcase of a computer on black friday. Also, to access the dataset please contact me on LinkedIn and I will give you access to the drive link.

About

Our aim was to find the relationship between number of purchases on Black Friday sales and variables such as occupation, marital status, age groups, gender, city category and number of years lived in a city. Another objective was to establish a market basket of items from product category A, B and C.

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