This repository contains three statistical analysis projects, each focusing on different aspects and methodologies within the field of statistics. Below is an overview of each project:
Summary:
- This project involves an in-depth exploratory data analysis, emphasizing data preprocessing, visualization, and initial statistical examination.
- Key aspects include data cleaning, handling missing values, and creating descriptive statistics to understand the dataset's characteristics.
- Various visualizations are used to highlight patterns and relationships within the data.
Summary:
- The focus of Project 2 is on advanced statistical modeling techniques.
- It covers the implementation of logistic regression models and examines the effects of various predictors on the outcomes.
- The project also delves into the utilization of mixed models, highlighting the impact of random effects in statistical analysis.
Summary:
- Project 3 explores the use of simulation-based methods alongside data-based approaches.
- It includes a detailed comparison of models derived from simulated data against models built from real datasets.
- The project also incorporates ROC-AUC analysis, providing insights into model performance and evaluation metrics.
Project-1-Report.pdf: Contains the full report for Project 1, including data exploration and preliminary analysis.Project2.pdf: Detailed report for Project 2, focusing on advanced statistical modeling techniques.Project-3-report.pdf: Comprehensive report for Project 3, showcasing the application of simulation methods and comparative analysis.
Each project report contains a thorough explanation of the methods used, the results obtained, and the conclusions drawn from the analysis. These projects collectively demonstrate a range of skills in statistical analysis, from basic exploratory techniques to more complex modeling and simulation approaches.