The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
🚀 Available for Statistical Analysis & Research Projects
I’m a PhD-qualified Statistician with 14+ years of experience in data analysis and academic research.
I help clients with:
• Survey data analysis (SPSS, R, Python)
• Hypothesis testing, regression, factor analysis
• Thesis, dissertation & research support
• Data visualization & interpretation
I focus on delivering accurate results, clear insights, and professional reports.
📍 Time Zone: IST (UTC +5:30)
🌍 Available for global clients
If you’re working on a research or data-driven project, feel free to connect!
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
We create eye-catching advertising banners and professional marketing visuals that help businesses attract customers and strengthen their brand presence. We also build smart automation solutions for WhatsApp, email, lead generation, and customer management to save time and grow your business.
Road Safety Analysis | Python, SQL & Power BI
Developed an end-to-end road safety analytics project to help authorities understand accident patterns, identify high-risk areas, and make informed decisions about road safety interventions.
The project involved cleaning and preparing road accident data using Python and Pandas, followed by SQL-based exploratory analysis to investigate accident trends, casualty figures, severity distributions, and geographical patterns.
Using Power BI, I transformed the findings into an interactive dashboard featuring key performance indicators and visualisations that provide an overview of accident activity, highlight trends over time, and reveal differences in accident occurrence across districts and locations.
The analysis also explored accident severity in relation to road types, weather conditions, lighting, and road surface conditions.
Tools used: Python, Pandas, SQL, Power BI.
Project deliverable: An interactive Power BI dashboard supported by data cleaning, transformation, and SQL analysis.
The objective was to turn raw accident data into clear, meaningful insights that can support evidence-based road safety planning and resource prioritisation.
A research data analysis and reporting demonstration showcasing the ability to organise experimental data, perform statistical analysis, interpret results and communicate scientific findings through tables, charts and structured reports.
