The Ordinal vs. Interval Debate in Psychology

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  • Опубликовано: 27 ноя 2024

Комментарии • 4

  • @bell_eau
    @bell_eau Год назад +1

    I made a questionnaire for my thesis and assumed my data as measured on an interval scale rather than ordinal in measuring outgroup moral perceptions. My tutor thought it was okay to do, so I went along with the procedure while actually not fully understanding what this decision implies. Hearing your perspective increased my understanding and I know better how to treat data and form appropriate conclusions for future projects! :-)

    • @PsychExamReview
      @PsychExamReview  Год назад +1

      Really glad to hear that my video helped with your understanding. All the best in your future research, definitely an interesting topic!

  • @denniswong5771
    @denniswong5771 8 месяцев назад

    I am facing the query when doing my research. I am inclined to YES because in the Olympic Games, for competitions like acrobatics, the judges are using some rating scales pf 10. And the contestants are graded. Even though there are schemes of deducting marks for missings, can the scores be really intervals? And we all agree a contestant scoring 78.6 is better than one with 78.1 and there goes the gold medal. So, why not for researches. Another point is that there are weightings for different movements. Such as 0.5 mark will be added extra to a 3m dive with 360 twist while that for 180 degree will have no additional marks. What's the interval difference between 360 twist than 180 twist? Why only 0.5 when 360 is 2 times of 180?

    • @PsychExamReview
      @PsychExamReview  8 месяцев назад

      I'm not well-informed on the criteria for specific competition scoring but even when these are detailed subjective elements remain and occasionally lead to controversy. In terms of research, treating many types of ordinal data as interval is accepted and being able to calculate a mean opens up a broad and very useful range of statistical analyses. But just because this is often fruitful doesn't mean that it's always acceptable and it's important to keep in mind that assumptions must be made in order to do this and these assumptions may not always be appropriate for some data. Thanks for commenting!