The article "Likert Scales: How To (Ab)Use Them?" by Jamieson (2004) discusses the appropriate use of Likert-type rating scales in educational research. Likert scales are commonly used to measure attitudes, typically with five response categories ranging from "strongly disagree" to "strongly agree." These scales fall under the ordinal level of measurement, meaning the response categories have a rank order but the intervals between values are not necessarily equal. However, many researchers incorrectly assume that Likert scales are interval-level, leading to the use of inappropriate statistical methods such as means and standard deviations, and parametric tests like ANOVA. The author highlights that for ordinal data, the median or mode should be used as the measure of central tendency, and non-parametric tests like Chi-square, Spearman’s Rho, or the Mann-Whitney U-test are more appropriate. Despite this, many authors, including those in Medical Education, continue to use parametric statistics with Likert data, often without clear justification. The article emphasizes the importance of considering the level of measurement and the appropriateness of statistical methods at the design stage of research. It concludes that while some argue that sample size and distribution are more critical than the level of measurement, others maintain that treating ordinal scales as interval scales can lead to incorrect conclusions. The author supports the argument that the average of 'fair' and 'good' is not 'fair-and-a-half,' even when integers are assigned to these categories.The article "Likert Scales: How To (Ab)Use Them?" by Jamieson (2004) discusses the appropriate use of Likert-type rating scales in educational research. Likert scales are commonly used to measure attitudes, typically with five response categories ranging from "strongly disagree" to "strongly agree." These scales fall under the ordinal level of measurement, meaning the response categories have a rank order but the intervals between values are not necessarily equal. However, many researchers incorrectly assume that Likert scales are interval-level, leading to the use of inappropriate statistical methods such as means and standard deviations, and parametric tests like ANOVA. The author highlights that for ordinal data, the median or mode should be used as the measure of central tendency, and non-parametric tests like Chi-square, Spearman’s Rho, or the Mann-Whitney U-test are more appropriate. Despite this, many authors, including those in Medical Education, continue to use parametric statistics with Likert data, often without clear justification. The article emphasizes the importance of considering the level of measurement and the appropriateness of statistical methods at the design stage of research. It concludes that while some argue that sample size and distribution are more critical than the level of measurement, others maintain that treating ordinal scales as interval scales can lead to incorrect conclusions. The author supports the argument that the average of 'fair' and 'good' is not 'fair-and-a-half,' even when integers are assigned to these categories.