Jamieson (2004) discusses the appropriate use of Likert-type rating scales in educational research. Likert scales are commonly used to measure attitudes, with responses typically ranging from "strongly disagree" to "strongly agree." However, the measurement level of Likert scales is often debated. While they are considered ordinal, there is a common assumption that they represent interval data, which can lead to inappropriate statistical analysis. The author argues that treating Likert scales as interval data is problematic because the intervals between response categories are not necessarily equal. This misinterpretation can result in the use of inappropriate statistical methods, such as parametric tests, which may lead to incorrect conclusions. The author highlights that for ordinal data, measures like the median or mode are more appropriate than the mean, and non-parametric tests should be used instead of parametric ones. Despite this, many authors, including those in Medical Education, often misuse Likert scales by reporting means and standard deviations and using parametric analyses. This practice is inconsistent with statistical guidelines and can undermine the validity of research findings. The author suggests that researchers should consider the level of measurement when designing studies and should clearly address the appropriateness of their statistical methods. Knapp (1990) argues that while the level of measurement is important, sample size and distribution are also critical factors in determining the suitability of parametric statistics. However, even if Likert data is treated as interval, the distribution of responses may be skewed or polarized, which can affect the validity of statistical conclusions. In conclusion, the author emphasizes the importance of correctly interpreting Likert scales and using appropriate statistical methods to ensure the quality of research in medical education. The misuse of Likert scales can lead to flawed conclusions, and researchers should be aware of the limitations and appropriate use of these scales.Jamieson (2004) discusses the appropriate use of Likert-type rating scales in educational research. Likert scales are commonly used to measure attitudes, with responses typically ranging from "strongly disagree" to "strongly agree." However, the measurement level of Likert scales is often debated. While they are considered ordinal, there is a common assumption that they represent interval data, which can lead to inappropriate statistical analysis. The author argues that treating Likert scales as interval data is problematic because the intervals between response categories are not necessarily equal. This misinterpretation can result in the use of inappropriate statistical methods, such as parametric tests, which may lead to incorrect conclusions. The author highlights that for ordinal data, measures like the median or mode are more appropriate than the mean, and non-parametric tests should be used instead of parametric ones. Despite this, many authors, including those in Medical Education, often misuse Likert scales by reporting means and standard deviations and using parametric analyses. This practice is inconsistent with statistical guidelines and can undermine the validity of research findings. The author suggests that researchers should consider the level of measurement when designing studies and should clearly address the appropriateness of their statistical methods. Knapp (1990) argues that while the level of measurement is important, sample size and distribution are also critical factors in determining the suitability of parametric statistics. However, even if Likert data is treated as interval, the distribution of responses may be skewed or polarized, which can affect the validity of statistical conclusions. In conclusion, the author emphasizes the importance of correctly interpreting Likert scales and using appropriate statistical methods to ensure the quality of research in medical education. The misuse of Likert scales can lead to flawed conclusions, and researchers should be aware of the limitations and appropriate use of these scales.