Data Sets Examples for Regression Analysis: Expand Your Data Science Portfolio

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Introduction

Regression analysis is a fundamental statistical technique used to understand the relationship between a dependent variable and one or more independent variables. It is widely used in various fields, including economics, finance, healthcare, and social sciences. To effectively learn and practice regression analysis, it is essential to work with real-world data sets. In this article, we will explore the top 21 regression data sets and projects that can help you enhance your data science portfolio.

Beginner Regression Datasets and Projects

If you are new to regression analysis, starting with beginner-friendly datasets is a great way to build your skills. The following are some examples:

Flowcast - Credit Card Fraud Detection Take-Home: This dataset focuses on predicting credit card fraud using regression techniques. It includes features like transaction amount, time, and various anonymized variables.
PCOS Diagnostic: This dataset is related to the diagnosis of Polycystic Ovary Syndrome (PCOS) in women. It includes features like age, BMI, glucose, and insulin levels.
Movie Revenue and Rating Prediction: This dataset involves predicting the revenue and rating of movies based on features like budget, genre, and cast.

Intermediate Regression Datasets and Projects

Once you have gained some experience with regression analysis, you can move on to more challenging datasets. Here are a few examples:

Fraud Detection: This dataset focuses on predicting fraudulent transactions in an e-commerce platform. It includes features like transaction amount, customer information, and product details.
Stock Price Prediction: This dataset involves predicting the future stock prices of a company based on historical data, market trends, and other relevant factors.
Wine Quality Classifier: This dataset aims to classify wines into different quality categories based on various chemical properties.

Advanced Regression Datasets and Projects

If you are ready for more advanced regression projects, the following datasets will provide you with a challenging learning experience:

Iris Flower Classification: This dataset is a classic example used for classification and regression analysis. It involves predicting the species of iris flowers based on their sepal and petal measurements.
Experience and Salary Analysis: This dataset explores the relationship between work experience and salary. It includes features like years of experience, education level, and job title.
Capgemini: Movie Revenue Prediction Take-Home: This dataset focuses on predicting the revenue of movies based on various features like budget, genre, and release date.

Conclusion

Regression analysis is a powerful tool for understanding and predicting relationships between variables. By working with diverse datasets and projects, you can enhance your regression analysis skills and expand your data science portfolio. Remember to always analyze and interpret your results critically to gain valuable insights. Happy regression modeling!

Learn more about Regression Models

If you are interested in learning more about regression models and their applications, check out the following resources:

Regression Analysis by Example, Third Edition - Chatterjee, Hadi, and Price
Data Files | SPSS Textbook Examples

More Data Science Project Ideas & Datasets

If you are looking for more data science project ideas and datasets, consider exploring the following:

Customer Ad Clicks
Global Temperature and Pollution
Who Will Survive the Titanic?
Air Quality Index Prediction
Online Shopper's Intention
Medical Cost Personal Datasets
ClearMotion: Vertical Acceleration Predictor Take-Home
Video Game Sales Prediction
Song Popularity Predictor
Human Activity Recognition
WHO Life Expectancy Dataset