Post Graduate Researchers from Statistics at University of Rajshahi, working in the Data Science Research Lab.
Academic statistical analysis
Statistical analysis you can explain under review.
We are a data analysis, mentorship, and research support team based at the University of Rajshahi. We help undergraduate, master’s, PhD students, and faculty members with clear research methods, clean analytical outputs, and practical explanations they can understand, use, and return to later.
R
Python
SPSS
Stata
ExcelWhy trust this
A group of researchers with Expertise in Statistics and Data Science.
Projects are matched by method, software, and subject fit, not assigned to whoever is free today.
All client-facing analysis notes get internal method review before they are sent out to you.
Full support for research and client workflows across R, Python, SPSS, Stata, and Excel each day.
Research team
Multiple researchers, one shared review standard.
stat.bd is not meant to depend on one person doing everything. Projects are scoped, matched to the right academic support role, and reviewed for method fit, clarity, and stated limits.
Matching by method
We read the topic, data, software, and deadline first, then assign the analyst whose methods fit the project.
Layered review
Before anything goes back to you, a second reviewer checks the method, how the results are read, and where the limits are.
Academic network
Several researchers work to one standard, so thesis, survey, manuscript, and revision work go to the right person.
Services
From messy data toward analysis you can explain in a viva or supervisor meeting.
Thesis and Dissertation Analysis
Questionnaire coding, descriptive analysis, reliability, regression, mediation, moderation, SEM/CFA/PLS where appropriate, and reporting suited for academic review.
Survey and Questionnaire Design Review
Scale choice, form logic, sampling checks, pilot feedback, and data-cleaning plans before analysis starts, including post-collection survey paths.
Manuscript and Revision Support
Method selection, journal-style tables, interpretation notes, reviewer-facing revisions, and reproducible output packaging.
Research Consultation
Project scoping with the right reviewer for students and researchers who need a practical analysis plan before committing to a larger project.
Two paths: analysis support or learning
Not sure where to start?
Choose the option that matches what you need right now.
Services
You have data, a deadline, and need analysis, tables, or statistical reporting for a thesis, survey, or manuscript.
Request a reviewMentorship
You want to learn statistics, software, or research methods in guided sessions—not hand off the analysis.
Request a learning planProcess
A four-step workflow with clear checkpoints.
Share the basics
Send the topic, data status, deadline, and software expectations. We check fit and whether the methods are clear enough to proceed.
Confirm the analysis plan
Agree on the question, method family, deliverables, revision boundary, and expected turnaround before work begins.
Run and explain
You receive tables, outputs, short interpretation notes, and an explanation of what was done and why.
Revise if needed
A scoped revision pass covers feedback, reviewer comments, or supervisor requests without restarting the whole project.
Boundaries
Clear scope matters as much as technical skill.
No fabricated results
We never invent data, manufacture findings, or take unethical shortcuts to reach a result.
No outcome guarantees
We do not promise publication, grades, viva outcomes, or approvals that depend on academic review.
No off-channel workflow
Project communication stays on email and the contact form. We do not route sensitive work through informal messaging apps.
FAQ
Answers before you send a project.
What should I send in the first message?
The research title, your department or university, where the data stands, any software you prefer, the output you need, and the deadline. A few lines is enough for an initial review.
Do you guarantee publication or thesis approval?
No. We focus on sound analysis and clear reporting. Academic review still depends on the study design, data quality, writing, and institutional requirements.
How is my data handled?
Project files are treated confidentially. Access is limited to the assigned analyst and reviewer. Working files are deleted within 30 days of project closure unless you request otherwise. Nothing is reused or shared publicly.
Which tools are supported?
Typical workflows include R, Python, SPSS, Stata, and Excel, depending on the project type and what you can reopen or explain later.
Is stat.bd one person or a team?
We are a research team backed by the Data Science Research Lab at University of Rajshahi. Requests are reviewed first, then routed to the statistics, survey, manuscript, or software role that fits.
What requests are refused?
Requests that require false claims, copied analysis without understanding, fabricated evidence, misleading presentation of results, or p-hacking are out of scope.
Next step
Start with the topic, the data status, and the deadline.
The first contact should make the project easier to evaluate. Send the core facts and the main decision you are blocked on.