Experimental Statistical Data Analysis
Experimental Statistical Data Analysis is an open source tool developed for experimental data analysis and visualization using advanced statistical techniques.
Key Features
- ANOVA Analysis: Implementation of analysis of variance for treatment comparison
- Tukey Test: Post-hoc analysis to identify significant differences
- Advanced Visualization: Statistical charts displaying differences between groups
- Result Export: Automatic saving of results to CSV files
- Open Source: Source code available for the scientific community
Technologies Used
- Language: R in RStudio
- Specialized Libraries:
- ggplot2 for advanced visualization
- dplyr for data manipulation
- readr for CSV file import
- multcompView for post-hoc tests and significance visualization
Achievements
Demonstrated proficiency in data handling and statistical result interpretation to support decisions based on experimental evidence.
Impact
This project evaluates experimental data through advanced techniques, including ANOVA and Tukey Test, generating visualizations that facilitate the interpretation of significant differences between experimental groups.
The tool focuses on comparing experimental treatments and generating clear visualizations that allow researchers to identify patterns and statistically significant differences in their data, contributing to evidence-based scientific analysis.
