Data Analysis Statistical Thinking

The data is about IBM Telco Customer Churn. The dataset is downloaded from Strivatsan88's Github Repo

Content

1. Title: IBM Customer Churn Dataset

2. Sources:

   Origin: This dataset was taken from Srivatsan88' YoutubeLI Github Repository. I downloaded the dataset in order to walkthrough the Youtube video published by AIEngineering, Statistical Thinking - Imputing Missing Values Date: October 10, 2021

Description of Data

The data is stored in the /dataset/orignal folder, where you can find customer_data.csv

Details on the original data:

• Number of instances: 7044

• Number of attributes: 10

• Attribute information:

  Attribute Name	Description	Attribute Type
  customerID	Unique ID of customer	Qualitative
  Gender	Gender of customer	Qualitative
  SeniorCitizen	Flag indicating if customer is a senior citizen	Multi-value discrete
  Tenure	Period of tenure	Continous
  ServiceCount	Number of service made by customer	Continous
  Contract	Type of contract for the service	Qualitative
  PaperlessBilling	Boolean indicating method of payment made by customer	Qualitative
  MonthlyCharges	Monthly charges for the services	Continous
  Churn	Boolean as label if customer churn	Qualitative

• Missing attribute values: The data exploration is not conducted yet.

Inspiration

Inspired by Data Analysis on Rozie's Dataset. I decided to sharpen my statistics to improve my analysis skills. This is sole for training purposes. Feel free to join along :)