3-Month Research Mentorship Program

Learn Research by Doing Your Own Research.

Want to do research, but not sure where to start? Or do you know some methodology, statistics, or SPSS, but still feel unsure how to use them in your own research? The Research Cohort was built for exactly these problems.

Register Now View the Full Syllabus

Register with the first month’s fee. We then assign your mentor and cohort based on your background.

Program length
3 months
Live classes
36
Students per cohort
3–5
Per month
BDT 4,000 BDT 2,500

Watch

A Short Introduction to the Research Cohort.

Who It Is For

Want to Start Research? Or Started and Got Stuck?

The Research Cohort is mainly for students and new researchers who want to learn research methodology and data analysis properly.

  • Undergraduate Students

    You want to do research for the first time but are not sure how to begin.

  • Master’s Students

    You have a thesis or research project ahead and want to learn research design and data analysis yourself.

  • New Researchers

    You work in a research team, or want to be part of research in the future.

  • Anyone Learning Statistics or Software

    You want more than running tests in SPSS or R: to understand the reasoning behind the methods and use them in your own research.

A smiling young woman in a green kameez and a printed scarf, holding up one finger.

How It Works

You Learn Together, but the Research Is Your Own.

Just three to five students study with one experienced mentor for three months. Everyone learns study design, sampling, and regression in the same class. How to use those methods in your own research is something each student works on separately, and the mentor reviews that work regularly.

One cohort might include:

  1. One student working on the mental health of university students.

  2. Another studying students’ academic performance.

  3. Someone else analyzing a social problem with a public dataset.

What You Will Learn

From the Basics of Research to Data Analysis.

The program has three parts: research methodology in the first month, statistics in the second, and software and data analysis in the third. There are 12 live classes each month, 36 in total.

  1. Month 1

    Research Methodology

    What you need to know before starting a study.

    Your work this month: Choose a research topic of your own and prepare its research question, objectives, study design, and a first study protocol.

    See Weeks 1–4

    Week 1: Getting Started

    • What research is and why it is done
    • How to read a research paper
    • Research problem and research question
    • Ways to find a good research topic

    Week 2: Planning the Research

    • Literature search and review
    • How to find a research gap
    • Research objectives and hypotheses
    • Types of study design and when to use each

    Week 3: Sampling and Measurement

    • Population and sample
    • Probability and non-probability sampling
    • The idea of sample size
    • Variables, measurement, and measurement scales

    Week 4: Study Protocol

    • Questionnaire and data collection plan
    • Research ethics
    • How to write a study protocol
    • Discussion and review of your own research idea

  2. Month 2

    Statistics for Research

    Not just how to run a test, but why you run it.

    Your work this month: Choose the statistical methods your research needs and prepare a data analysis plan.

    See Weeks 5–8

    Week 5: Descriptive Statistics

    • Data types and measurement scales
    • Mean, median, and mode
    • Variance and standard deviation
    • Distribution, skewness, and outliers

    Week 6: Statistical Inference

    • Probability and sampling distributions
    • Standard error
    • Confidence intervals
    • The core idea of hypothesis testing

    Week 7: Statistical Tests

    • What a p-value actually tells you
    • t-test and chi-square test
    • ANOVA and other common tests
    • Which test to use in which situation

    Week 8: Correlation and Regression

    • The difference between correlation and regression
    • Basics of linear regression
    • Model assumptions
    • How to interpret statistical results

  3. Month 3

    Software and Data Analysis

    Now it is time to work hands-on with data.

    Your work this month: Complete the analyses your project needs and write a first draft of its methods and results.

    See Weeks 9–12

    Week 9: Data Preparation

    • Getting started with the software
    • Data import and variable setup
    • Data cleaning
    • Missing values and data checks

    Week 10: Practical Data Analysis

    • Descriptive analysis
    • Statistical tests
    • Correlation and regression analysis
    • Working through your own analysis plan

    Week 11: Results and Interpretation

    • Building results tables
    • Making graphs and figures
    • Reading statistical output
    • How to write up and interpret results

    Week 12: Final Project Review

    • Putting your project’s analysis in order
    • Writing the methods and results
    • Discussing the project’s limitations
    • Final project review and feedback

Parts of the syllabus may change to fit the research topics and needs of the students in a cohort. How much of the project you complete depends on your regular participation and practice, the data available, and the type of study.

No Research Topic Yet? That Is Fine.

If you already have a research idea, you can work on it. If you have no idea yet, we help you turn a subject you care about into a good research question.

Say you want to know:

Is university students’ study time related to their exam results?

That question can become a study. But first you need to settle a few things:

  1. Which students will you study?

  2. How many people’s data will you need?

  3. How will you measure study time and exam results?

  4. Which statistical method will you use?

  5. If you find a relationship, can you say that studying more caused the better results?

Working through questions like these is how you learn to do research.

If you have no data of your own, you can work with a suitable public dataset.

Not Just Classes: Time for Your Own Research Too.

A method that looks simple in class can feel much harder on your own data. So your work is followed outside class too.

A smiling young woman in a green kameez with a yellow flower in her hair, arms folded, outdoors.

12

Live Classes a Month

Each class covers a set topic, explained with real examples, research papers, and datasets.

1:1

Project Review Every Two Weeks

A one-to-one discussion of your project with the mentor. Whether the problem is in your study design, your choice of method, or your data analysis, that is what you talk through.

Weekly Question and Discussion Slot

If something from class is unclear, or you get stuck while practicing, you can ask at a set time each week.

Practice and Assignments

Short, regular tasks help what you learn stick. Some use a set dataset, and some are tied to your own project.

Published Papers and Real Datasets

Relevant papers and real data show where and how each method is used, so you learn not only how to run the software, but how researchers make their decisions.

Who Teaches

Learn Research From People Who Do Research.

Stat.BD was started by a few young researchers connected to the Department of Statistics and Data Science at the University of Rajshahi. Our team members work in research methodology, statistical analysis, survey research, machine learning, and many kinds of applied research.

When we teach, we focus on the problems we run into in our own research. Beyond what a textbook says about a method, we discuss why it is used in real studies and where mistakes are likely.

Each cohort has one mentor, chosen to match the students’ interests and the type of research.

About Our Team

Stat.BD is an independent research and mentorship initiative. This is not an official course or degree program of the University of Rajshahi.

Certificate

Attending Is Not Enough: The Work Must Be Finished Too.

Students who complete the Research Cohort receive a verifiable Certificate of Completion from Stat.BD. Attending classes alone does not earn it: you need to finish the set work on your research project and meet the conditions of the mentor’s review.

Each certificate has a unique ID and QR code for verifying it online.

Sample certificate. Yours shows your name, cohort details, mentor’s name, program dates, and the title of your completed project.

Student Reviews

What Students Say

In their own words, including what they think we should do better.

  • My main issue with online courses has always been that I finish watching everything and then forget half of it when I actually need to use it. Had a similar problem in the beginning here too. I think the course could benefit from more follow-up assignments and feedback. But I did learn how to approach a research question and plan the analysis instead of randomly trying different tests. Still not an expert obviously, but definitely more confident than before.

    Samin Farhan

  • থিসিসের ডেটা কালেকশনের পর প্রায় একমাস কিছু করতে পারি নাই। কোথা থেকে শুরু করব সেটাই বুঝতাম না। Stat.BD থেকে শেখার পর অন্তত নিজের অ্যানালাইসিসটা শুরু করতে পেরেছি। আগে সুপারভাইজার মেথড নিয়ে কিছু জিজ্ঞেস করলে ভয় লাগত। এখন সব না পারলেও নিজের কাজটা মোটামুটি বুঝিয়ে বলতে পারি। আমার জন্য এটাই অনেক।

    আরিবা নাওয়ার

  • Stat.BD এর teaching approach ভালো লেগেছে। But I think assignment গুলা আরেকটু challenging হওয়া উচিত। কারণ practice dataset এ সবকিছু মোটামুটি clean থাকে, নিজের research data তো এত clean না ভাই 🙂 প্রথমবার নিজের dataset নিয়ে বেশ ঝামেলায় পড়ছিলাম। যদিও এখন অনেক কিছু নিজে solve করতে পারি। Overall fundamentals clear করার জন্য ভালো, but advanced level এ যেতে আরো practice লাগবে।

    রাফিদ আদনান

  • Good course overall, but I wish there were more exercises with messy real-world datasets. The examples during class made sense, but when I tried my own data it wasn't that straightforward lol. That being said, the explanations of statistical tests and assumptions were genuinely helpful. I now understand a lot of things that I used to just memorize for exams.

    Zayyan Rahman

  • আমার কাছে কোর্সের সবচেয়ে ভালো দিক ছিল যে শুধু SPSS শেখানোর মধ্যে সীমাবদ্ধ ছিল না। রিসার্চের প্রশ্ন থেকে শুরু করে অ্যানালাইসিস পর্যন্ত একটা ধারনা পেয়েছি। তবে একটা বিষয় বলব, কিছু টপিকের পরে আরও বেশি প্র্যাকটিস করানো দরকার। কারণ ক্লাসে বুঝলেও বাসায় এসে একা করতে গেলে আবার আটকে গেছি কয়েকবার। তারপরও আগের তুলনায় অনেক ভালো অবস্থায় আছি।

    সাফওয়ান মাহির

  • I joined mainly for my thesis, and I was expecting more of a software training course. The first few sessions were a bit too theoretical for me tbh. But later I realised why those basics were important. I had previously watched tons of tutorials, still couldn't decide which test to use on my own data. I wouldn't say I can do everything independently now, but I can at least figure out what I'm supposed to do and why. That's a pretty big improvement for me.

    Anika Nawar

  • ভালোই ছিল কোর্সটা। তবে যারা একদমই স্ট্যাটিস্টিকস জানে না তাদের শুরুতে একটু সমস্যা হতে পারে। আমারও প্রথম কয়েকটা ক্লাস বুঝতে কষ্ট হইছে। পরে রেকর্ডিং আর প্র্যাকটিস করে বুঝছি। আসলে শুধু ক্লাস করলে হবে না নিজে ডেটা নিয়ে বসতে হবে। এই জিনিসটা আগে বুঝলে আরো ভালো হতো।

    তাহসিন রেদোয়ান

  • I liked the course but honestly সবকিছু যে একবারেই বুঝেছি এমন না। Especially regression part টা আমার কাছে একটু difficult ছিল। আর কিছু জায়গায় আরো examples দিলে ভালো হতো। But the good thing is, এখন অন্তত জানি analysis করার আগে কি কি চিন্তা করতে হয়। আগে শুধু YouTube দেখে SPSS এ click করতাম, output আসতো কিন্তু বুঝতাম না 😭 এখন নিজের thesis এর জন্য কাজ করতে পারছি আলহামদুলিল্লাহ।

    সামিহা তাসনিম

  • একটা জিনিস বলি, আগে ভাবতাম research মানেই অনেক complex কিছু, আমার দ্বারা হবে না। Stat.BD করার পর এই ভয়টা কিছুটা কমছে। এখন paper পড়ার সময় methodology section skip করি না আগের মতো 😂

    তবে class এর বাইরে individual feedback আরেকটু বেশি পেলে ভালো হতো। কিছু জায়গায় নিজে try করতে গিয়ে আটকে গেছি। But overall experience positive ছিল।

    আফরা মাহজাবিন

  • সত্যি বলতে আমি আগে SPSS এর অনেক টিউটোরিয়াল দেখছি, কিন্তু নিজের থিসিসের কাজ করতে গিয়ে বুঝলাম আসলে কিছুই ঠিকমতো শিখি নাই 😅 Stat.BD এর ক্লাসগুলো করে বেসিক জিনিসগুলো অনেকটা ক্লিয়ার হইছে। বিশেষ করে কোন টেস্ট কেন করব এটা আগে বুঝতাম না। এখন নিজের ডেটা নিয়ে কাজ করতে পারছি। তবে কিছু ক্লাস একটু ফাস্ট মনে হইছে, নতুনদের জন্য আরেকটু স্লো হলে ভালো হতো।

    মাইশা জারিন

How to Enroll

Register in One Step. We Take It From There.

  1. Register and Pay

    Confirm your email with a code we send. Then tell us what you study, whether you have done research before, and what you want to learn, and give the transaction ID of your first month’s fee on the same form.

  2. We Confirm Your Seat

    We check the payment against our statement and confirm your seat by email.

  3. We Assign Your Mentor and Cohort

    From your background, we choose your mentor and cohort. Each cohort brings together students at a similar stage with similar interests. Then we share the class schedule.

Frequently Asked Questions

I have never done research before. Can I join?

Yes. The program is designed so that complete beginners can learn from the start. We do try to keep the students in a cohort at a similar stage.

Do I need to know SPSS or R already?

No. Learning the software is part of the program. Having a computer for regular practice is a good idea, though.

Will SPSS, R, and Stata all be taught?

No. A cohort usually works with one main software package. Which one is decided by what the cohort’s students need.

How many days a week are classes?

There are 12 live classes a month, so usually three a week. The exact days and times are shared when the cohort is finalized.

Will my research paper be published in three months?

This is not a paper publication service. We teach research methods, analysis, and the writing process.

How far your own research gets in three months depends on your topic, your data, and your work. We do not guarantee publication.

Do I have to pay the full amount at once?

No. The fee is paid monthly: BDT 2,500 a month. The first month’s fee is your registration; you pay the remaining months from your account.

What happens after I register?

We check your payment and confirm your seat by email, usually within a few hours. Then we assign your mentor and cohort based on your background and share the class schedule.

A smiling young woman in a green kameez pointing to the side.

Want to Learn Research? Start Here.

For three months, you take classes in a small group, learn from real research, and work on a project of your own. If you want to learn and do research yourself, not just treat it as a course subject, this program is for you.

Stat.BD · Learn Research by Doing Research.

Register for the Research Cohort
Stat.BD