Bridging the gap between complex statistical methods and biological interpretation
StickForStats is a comprehensive statistical analysis platform designed to enable researchers with minimal statistical background to perform advanced analyses. The app intelligently suggests appropriate statistical tests based on data distribution and research questions, providing tools for experimental design, data analysis, and result interpretation.
Born from the observation that many researchers struggle with statistical analysis despite its critical importance in scientific research, StickForStats aims to democratize advanced statistical methods by making them accessible through an intuitive interface and clear explanations.
Current Status: Final development stages, with plans to deploy publicly in September/October 2024.
Automatically analyzes your data and research questions to recommend the most appropriate statistical tests
Helps design robust experiments with sample size calculations and randomization strategies
Creates publication-quality figures with customizable options for different analyses
Shows underlying R/Python code to promote reproducibility and learning
Automatically analyzes your data's characteristics and research questions to recommend the most appropriate statistical tests, eliminating confusion about which test to use.
Comprehensive learning tools like the Confidence Intervals Explorer that provide deep understanding of statistical concepts through interactive visualizations and simulations.
Helps researchers design robust experiments with appropriate sample sizes, power calculations, and randomization strategies to ensure statistical validity.
Creates publication-quality visualizations that clearly communicate your findings, with customizable options for different data types and analyses.
Shows the underlying R or Python code for each analysis, promoting reproducibility and helping users learn statistical programming over time.
Generates comprehensive reports with properly formatted results, appropriate citations, and interpretations tailored to your field of research.
Coming Soon: September 2024
Coming Soon: October 2024
The Principal Component Analysis module allows researchers to upload datasets, perform PCA with automatic preprocessing, visualize results with customizable 2D/3D plots, and generate publication-ready figures.
Try PCA ModuleExplore common statistical distributions interactively, understand how parameters affect distribution shapes, fit distributions to your data, and calculate probabilities and critical values.
Try Distributions ModuleUnderstand the theoretical foundations of confidence intervals through interactive simulations, visualize how sample size affects precision, and compare frequentist and Bayesian approaches.
Try CI ExplorerInitial concept development and prototype design of the StickForStats platform.
Development of key modules including PCA and Probability Distributions, released as standalone demos.
Combining individual modules into a unified platform with consistent UI/UX and shared data processing pipeline.
Internal testing with IGIB researchers to gather feedback on usability and feature completeness.
Initial public release of the StickForStats platform with core functionality and documentation.
Adding advanced modules, building user community, and incorporating feedback from the scientific community.
Researchers conducting wet-lab experiments who need to analyze their data without extensive statistics training. StickForStats helps with experimental design, sample size calculation, and appropriate statistical analysis of results.
Example: A molecular biologist comparing gene expression changes across multiple treatment conditions can use StickForStats to determine the appropriate statistical test, perform the analysis, and generate publication-ready figures.
Medical professionals conducting clinical studies who need robust statistical methods for patient data. StickForStats provides specialized tools for survival analysis, repeated measures, and other clinical research methods.
Example: A clinical researcher studying drug efficacy can use StickForStats to perform power analysis for study design, analyze treatment outcomes with appropriate controls for confounding variables, and generate comprehensive reports.
Students in biology, medicine, and related fields who need to analyze their thesis data but lack formal statistical training. StickForStats serves as both an analysis tool and an educational resource.
Example: A PhD student can not only analyze their data but also learn statistical concepts through the interactive tutorials and code transparency, building valuable data science skills.
StickForStats aims to democratize advanced statistical analysis by making complex methods accessible to researchers of all backgrounds. Our vision includes:
We believe that by making advanced statistical tools more accessible, we can help researchers focus on their scientific questions rather than struggling with statistical methods, ultimately accelerating discovery and improving research quality.
StickForStats is an open-source project, and we welcome contributions from the community:
Help develop new modules, improve existing functionality, or fix bugs. We welcome contributions from developers of all skill levels.
GitHub RepositoryTry our beta versions and provide feedback on functionality, usability, and features that would benefit your research.
Request Beta AccessHelp improve tutorials, documentation, and educational resources to make the platform more accessible.
Contact UsWhether you're interested in using StickForStats for your research, contributing to the project, or discussing potential collaborations, I'd love to hear from you.