LESSON 41 - LIKERT SCALE || WHAT IS LIKERT? || DOES IT COLLECT CONTINUOUS OR CATEGORICAL DATA?

LESSON 41 - LIKERT SCALE || WHAT IS LIKERT? || DOES IT COLLECT CONTINUOUS OR CATEGORICAL DATA?

by Prof. Lydiah Wambugu

Humanities, Social Sciences & Thought Science — General & History GPSResearch methodsGPSDQuantitative research methods
🎙 Prof. Lydiah Wambugu 👥 29K 📅 July 24, 2021 ⏱ 12 min 👁 4K 📄 tutorial 🧭 2026-08-17
Available in: English (current) Français

Keywords

Likert scalecategorical datacontinuous dataquestionnaireresearch methods

Summary

This lesson introduces the Likert scale, a tool for collecting quantitative data on attitudes. It explains that Likert scales typically use a five-point scale (strongly agree to strongly disagree) and that the decision to treat the data as categorical or continuous must be made during questionnaire design. For categorical data, responses are analyzed as ordinal (using modes and frequencies), while for continuous data, they are treated as interval (using means and standard deviations). The instructor provides guidelines for constructing Likert items, such as using short simple statements, avoiding factual statements and double negatives, balancing positive and negative items, including at least 10 statements, and avoiding double-barreled questions. Finally, the lesson debunks three common myths: that scale items are independent, that they should be analyzed separately, and that little expertise is needed to construct them. The instructor emphasizes that Likert items are interrelated and should be analyzed together to address a variable.

151 words

Critical Evaluation

Value of the Information & Strength of the Argument

The video provides a clear and practical introduction to Likert scales, emphasizing the critical distinction between categorical and continuous data analysis. The argumentation is logical and well-structured, with concrete examples for each guideline. The instructor effectively explains why the data analysis approach must be decided in advance, which is a key insight for students. The myths section is valuable as it addresses common misconceptions. However, the video lacks depth in discussing statistical techniques beyond basic measures, and the argumentation would benefit from references to methodological literature.

Scientific Rigor, Source Quality, Title Accuracy

The scientific rigor is moderate: the content is accurate but presented without citations to external sources, relying solely on the instructor’s expertise. The guidelines align with standard research methods textbooks, but no specific references are provided. The title accurately reflects the content, which is a tutorial on Likert scales. The description includes links to the instructor’s website and social media, but these are not academic sources. No comments were provided for analysis.

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Title / Content Match

The title accurately reflects the content, which covers the definition, data type, construction guidelines, and myths about Likert scales.

Quality & Reliability

7/10

The content is accurate and well-structured, but lacks citations to external sources and relies on the instructor's expertise. The distinction between categorical and continuous data is correctly explained, and guidelines are practical.

Key Moments

Markers derived by PSI from the transcript: the creator did not define chapters.

Cited Sources

  • Research Methods Course — Mentioned as the full course where this lesson is part of.
  • YouTube Channel — Link to subscribe to the channel.
  • LinkedIn — Social media link for following the instructor.
  • Facebook — Social media link for following the instructor.
  • Instagram — Social media link for following the instructor.
  • Live Chat — WhatsApp link for consultation.

Concurring Sources

Contribution & Novelties

The video offers a concise and accessible explanation of Likert scales, particularly emphasizing the often-overlooked decision between categorical and continuous data analysis. It provides practical guidelines for constructing items and debunks common myths, which is valuable for students. However, it does not introduce novel concepts beyond standard research methods knowledge.

Pour aller plus loin :

104 words

Radar Profile

The radar profile shows a balanced performance across all dimensions, with slightly higher scores in information quantity and reliability, and slightly lower in technical level. This indicates a solid introductory tutorial that is accessible but not deeply technical.

Reliability 7/10