Human Body Morphology Analysis

---

Project Description

This project is part of the final exam at Statistics course and showcases the skills learned through the subject. I used advanced statistical analysis techniques to investigate the relationship between weight and various morphological variables based on human body morphology data.

Project Content

Objectives

• Analyze the relationship between weight and morphological variables.
• Utilize non-parametric regression techniques and regularization methods in linear models.

Project Stages

1. Data Reading

   • Data loading from the body.xls file.
   • Verification and control of data integrity.

2. Exploratory Stage

   • Estimation of weight median by gender and calculation of confidence intervals using bootstrap.
   • Exploratory analysis of the relationship between height and weight, discriminating by gender.
   • Adjustment of non-parametric regressions and search for the optimal bandwidth.

3. Linear Regression

   • Fitting linear models using all explanatory variables.
   • Selection of significant covariates without multicollinearity.
   • Application of LASSO regularization method.

4. Model Evaluation

   • Evaluation of empirical prediction error in the test group.
   • Final conclusions and recommendations.

Technologies Used

• R
• RStudio
• Libraries: readxl, ggplot2, caret, glmnet

Achievements

• In-depth analysis of complex human body morphology data.
• Application of advanced statistical analysis techniques.
• Clear and concise presentation of results.

Why is this Project Relevant?

• Demonstrates my ability to tackle complex data analysis problems.
• Shows my experience in using advanced statistical techniques.
• Highlights my ability to extract meaningful information from large and complex datasets.