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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.