https://github.com/jendives2000/regressions

Performing of a Linear Regression analysis to determine the strength of the relationship between the number of reviews and sales for a retail company.
https://github.com/jendives2000/regressions

data-analysis linear-regression pearson-correlation-coefficient regression

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Performing of a Linear Regression analysis to determine the strength of the relationship between the number of reviews and sales for a retail company.

• Host: GitHub
• URL: https://github.com/jendives2000/regressions
• Owner: jendives2000
• Created: 2024-08-24T16:37:19.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-09-15T07:05:33.000Z (5 months ago)
• Last Synced: 2025-01-22T01:01:36.517Z (8 days ago)
• Topics: data-analysis, linear-regression, pearson-correlation-coefficient, regression
• Language: Jupyter Notebook
• Homepage:
• Size: 358 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Project Description: 

## Practice Exercise #2:  

You are working as a data scientist for a **retail company**. The management wants to: 

*   understand the relationship between:

    - the number of online customer reviews for a product

    - and the monthly sales figures for that product.

**They believe that more reviews should correlate with higher sales** but want to quantify this  

relationship to guide marketing strategies.  

### Objectives  

1.   Determine the stength of the relationship between:  

    - the number of customer reviews (independent variable 𝑋)  

    - and monthly sales (dependent variable 𝑌).

     

2.   Present your conclusions and recommendations

### Dataset:  

The dataset was **randomly created using pandas**, this ensures we do **not bring bias** into the set.  

It has 120 rows.  

## Practice Exercise #1:  

You are a data scientist working for an e-commerce company.  

The marketing team wants to:  

*   understand the relationship between:

    - the amount of money spent on online advertising

    - and the revenue generated from those ads

**They believe that more spendings on ad should correlate with higher revenues** but want to quantify this  

relationship to guide marketing strategies.  

### Objectives  

1.   Determine the stength of the relationship between:  

    - the amount of money spent on online advertising (independent variable 𝑋)  

    - and the revenue generated from those ads (dependent variable 𝑌).

     

2.   Present your conclusions and recommendations

### Dataset:  

The dataset was uploaded from an external source as part of a specialized course.

It has 10 rows.  

# Methodology:

For relationship strength evaluation between 2 variables, the **Pearson correlation coefficient** is the way to go.  

For practice and memorization purposes, I added the **mathematical formula** whenever it is needed using the **LaTex** language.  

For calculations I used the **numpy library**.

For visualizations, I used **matplotlib and scipy** to add the function itself.

# Contact me:

*   LinkedIn: https://www.linkedin.com/in/jytran-datascience

My name is Jean-Yves TRAN, I bring 9 years of promotional video creation and project management into Data. My goal is to  

first become an ML Engineer and leverage that experience to mature into a Data Scientist.