Multivariate Analyisis

Welcome to my notes on multivariate statistical analysis! As a data scientist, I have found that understanding and applying multivariate statistical techniques is essential for extracting insights from complex datasets. These notes are my personal collection of key concepts, techniques, and practical applications that I have learned and used over the years.

My goal in creating these notes is to provide a useful resource for myself to review and reference in the future, as well as to share my knowledge with others who are interested in learning about multivariate statistical analysis. Whether you are just starting out in the field or have years of experience, I hope you will find these notes to be a valuable reference and a source of inspiration for your own work.

Throughout these notes, I will cover a range of topics related to multivariate statistical analysis, including exploratory data analysis, principal component analysis, factor analysis, clustering, discriminant analysis, and more. I will provide clear explanations of key concepts, step-by-step instructions for implementing techniques in Python, and real-world examples to demonstrate how these techniques can be used to extract insights from complex datasets.

I invite you to join me on this journey through the world of multivariate statistical analysis. Let’s explore together how these powerful techniques can be used to unlock the hidden patterns and relationships in data, and turn raw data into actionable insights.

Lastly, I would like to add that if you find any errors, please do not hesitate to contact me through LinkedIn. I would be very grateful for your feedback.