Cardio fitness project - preliminary data analysis

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Reference no: EM132386912

Cardio Fitness Project

Objective - Preliminary Data Analysis. Explore the dataset and practice extracting basic observations about the data. The idea is for you to get comfortable working in R.

You are expected to do the following :

1. Come up with a customer profile (characteristics of a customer) of the different products
2. Perform uni-variate and bivariate analyses
3. Generate a set of insights and recommendations that will help the company in targeting new customers

Context - The data is for customers of the treadmill product(s) of a retail store called Cardio Good Fitness. It contains the following variable
1. Product - the model no. of the treadmill
2. Age - in no of years, of the customer
3. Gender - of the customer
4. Education - in no. of years, of the customer
5. Marital Status - of the customer
6. Usage - Avg. # times the customer wants to use the treadmill every week
7. Fitness - Self rated fitness score of the customer (5 - very fit, 1 - very unfit)
8. Income - of the customer
9. Miles- expected to run

Explore the dataset to identify differences between customers of each product. You can also explore relationships between the different attributes of customers. You can approach it from any other line of questioning that you feel could be relevant for business.

Minimum Steps for exploration:
1. Importing the dataset into R & understanding the structure of a dataset
2. Basic summary of data and graphical exploration
3. Observations from the dataset

Project Objective

The objective of the report is to explore the cardio data set ("CardioGoodFitness") in R and generate insights about the data set. This exploration report will consists of the following:
Importing the dataset in R
Understanding the structure of dataset
Graphical exploration
Descriptive statistics
Insights from the dataset

Exploratory Data Analysis - Step by step approach
A Typical Data exploration activity consists of the following steps:
1. Environment Set up and Data Import
2. Variable Identification
3. Univariate Analysis
4. Bi-Variate Analysis
5. Missing Value Treatment (Not in scope for our project)
6. Outlier Treatment (Not in scope for our project)
7. Variable Transformation / Feature Creation
8. Feature Exploration

Environment Set up and Data Import

1. Install necessary Packages and Invoke Libraries
Use this section to install necessary packages and invoke associated libraries. Having all the packages at the same places increases code readability.

2. Set up working Directory
Setting a working directory on starting of the R session makes importing and exporting data files and code files easier. Basically, working directory is the location/ folder on the PC where you have the data, codes etc. related to the project.

Attachment:- Project - Cardio Good Fitness.rar

Reference no: EM132386912

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