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researcher should not increase assumptions than minimum

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June 2015 (II)

researcher should not increase assumptions than minimum

  • April 9, 2025
  • Com 0

The principle that a researcher should not increase assumptions than the minimum required is referred to as: 

(A) sample quota

(B) test sample

(C) occam’s razor

(D) golden mean

Correct Ans: (C)

Explanation:
Occam’s Razor is a principle that guides researchers and thinkers to keep things simple. It says: do not make more assumptions than necessary. In other words, when faced with multiple explanations, choose the one that requires the least speculation.

This idea helps cut through complexity. It encourages clarity, precision, and logical thinking. Researchers use it to avoid overcomplicating theories or adding unnecessary variables. The goal is to stay focused on what can be tested, proven, or observed directly.

Occam’s Razor doesn’t mean that the simplest explanation is always correct. Instead, it suggests starting with the least complex theory first. If evidence supports it, there’s no need to add extra layers. If not, researchers can then explore more complex alternatives.

In mass communication research, this principle is valuable. It helps simplify models, clarify data interpretations, and avoid biased conclusions. Whether studying audience behavior, media effects, or communication patterns, using Occam’s Razor keeps research grounded and practical.

This principle also encourages critical thinking. It reminds scholars to question assumptions and avoid unnecessary jargon or complexity. Clear, simple reasoning often leads to better understanding and stronger results.

In short, Occam’s Razor is about staying sharp with logic. It’s a timeless tool that pushes researchers to seek truth through clarity—not confusion.

Assistant Professor
Dr. Ranjan Kumar

Founder & Educator

Tags:
communication theorycritical thinkinglogicMass CommunicationOccam's RazorResearch Methodssimplicity in research
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Dr. Ranjan Kumar

Founder & Educator

Sarvodaya movement in Sri Lanka adopted model
A possible, but incorrect explanation of research results is called: 

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