Let’s be honest: studying Research Methods can feel like you’re learning how to build a house while everyone else is just talking about the furniture. It is the “how-to” of science. It’s the difference between having an opinion and having evidence.
Below is the exam paper download link
Past Paper On Research Methods For Revision
Above is the exam paper download link
In the exam hall, the professors aren’t just checking if you know what a “survey” is. They are testing your logical rigor. Can you spot a biased sample from a mile away? Do you know why a “p-value” can make or break a multi-million dollar study? Can you design an experiment that actually proves what it claims to prove?
The secret to moving from “confused” to “investigator” is active revision. Using past papers allows you to see the “trap” questions—the ones where a tiny change in a study’s design changes the entire statistical outcome. To help you sharpen your analytical lens, we’ve tackled the high-yield questions that frequently anchor Research Methods finals.
FAQ: Mastering the Science of Discovery
1. What is the actual difference between “Qualitative” and “Quantitative” research?
This is the foundational question of every paper.
Quantitative (The Numbers): Think of this as the “What” and “How Many.” It uses structured tools like surveys to produce statistics.
Qualitative (The Story): This is the “Why” and “How.” It uses open-ended interviews or observations to understand human experiences and meanings.
Exam Tip: If the question asks about “Generalizability,” the answer is almost always Quantitative. If it asks about “Depth,” it’s Qualitative.
2. How do I distinguish between “Independent” and “Dependent” variables?
Think of it as Cause and Effect.
Independent Variable (IV): This is the one you change or control (e.g., the dosage of a drug).
Dependent Variable (DV): This is the one you measure to see if the change worked (e.g., the patient’s blood pressure).
Pro-tip: If you see a third variable that messes up the relationship, call it a “Confounding Variable.” Examiners love that term.
3. What is the “Null Hypothesis” ($H_0$) and why do we try to reject it?
In science, we start by assuming nothing happened. The Null Hypothesis says: “There is no relationship between these two things.” Our goal is to find enough evidence to say, “Actually, the Null is wrong.” We don’t “prove” our idea is right; we just prove that the “nothing happened” idea is highly unlikely.
4. How do I choose between “Probability” and “Non-Probability” sampling?
Probability (Random): Everyone has an equal chance of being picked. This is the gold standard for avoiding bias.
Non-Probability (Convenience): You pick whoever is available (like students in your hallway). It’s faster and cheaper, but you can’t claim your results represent the whole world.
Your Revision Strategy: The “Reviewer” Mindset
Don’t just read the paper provided below; use it to “audit” hypothetical studies.
The policy-page-at-mpya-news/" title="Ethics">Ethics Check: For every study design in the past paper, check for Informed Consent and Anonymity. If a study involves vulnerable groups (like children or prisoners) without extra protections, point it out!
The “Reliability vs. Validity” Drill: Reliability is about consistency (does the scale give the same weight every time?). Validity is about accuracy (is the scale actually measuring weight or is it measuring height?). You need both to pass.
Timed Design: Practice writing a 200-word “Research Proposal” for a random topic (e.g., “Does coffee improve exam scores?”). Include your Aim, Hypothesis, Methodology, and Ethical considerations.
Download Your Revision Toolkit
Ready to see if you have the analytical brain required for a research final? We’ve sourced a comprehensive past paper that covers the fundamental principles of study design, data collection, and ethical research.
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Last updated on: March 6, 2026
New information gained / new value takehome
- Exam Tip: If the question asks about “Generalizability,” the answer is almost always Quantitative.
- Pro-tip: If you see a third variable that messes up the relationship, call it a “Confounding Variable.
- It’s faster and cheaper, but you can’t claim your results represent the whole world.
This content was developed using AI as part of our research process. To ensure absolute accuracy, all information has been rigorously fact-checked and validated by our human editor, Collins Murithi.
External resource 1: Google Scholar Academic Papers
External resource 2: Khan Academy Test Prep
Reference 1: KNEC National Examinations
Reference 2: JSTOR Academic Archive
Reference 3: Shulefiti Revision Materials
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