Yipsian Delgado I advocate for adopting ratio measurement in quantitative resear

Yipsian Delgado
I advocate for adopting ratio measurement in quantitative research. The choice for ratio measurement is based on its unique ability to offer a comprehensive quantitative analysis, which may be attributed to its fundamental qualities. In contrast to nominal and ordinal measures, which provide categorized and ranking data, ratio measurement enhances the accuracy of interval measurement by including a reasonable zero point.
This particular attribute improves the precision and dependability of data, enabling more intricate analysis, such as the computation of ratios, and therefore aiding in producing more thorough understandings (Cooksey,2020). In such studies, zero value represents either an absence or a baseline measurement. The utilization of ratio measurement enables the assessment of both relative and absolute disparities, hence augmenting the comprehensiveness (Marateb et al.,2014).
When data exhibits category or ordinal characteristics, it is both suitable and imperative to employ nominal and ordinal measurements, respectively. However, ratio measurement is particularly noteworthy in quantitative research that seeks to conduct a thorough and precise analysis, mainly when the nature of the data allows for it. This is due to its ability to provide intricate insights informed by its distinctive features such as a rational zero point, properties of interval data, and the potential for a more extensive statistical analysis.
References
Cooksey, R. W. (2020). Descriptive Statistics for Summarising Data. Illustrating Statistical Procedures: Finding Meaning in Quantitative Data, 61. https://doi.org/10.1007/978-981-15-2537-7_5
Marateb, H. R., Mansourian, M., Adibi, P., & Farina, D. (2014). Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies. Journal of Research in Medical Sciences : The Official Journal of Isfahan University of Medical Sciences, 19(1), 47.
Yeniffer Cruz
Levels of measurement in quantitative research are referred to as the different ways in which a variable can be calculated. There are some limitations to consider when selecting what level of measurement to use for a study, as some of them do not have the capacity to compute outside certain barriers. My preferred level of measurement would be ratio measurement, due to the fact that it provides the most precise answer.
According to an article by the Surveysparrow, It tells you about the order and the equal distance between two adjacent values. The zero in the ratio scale also has a lot of relevance. It tells the difference between “how much” (Williams, 2022). Ratio measurement allows for the estimation of a range between 2 variables, such as height, weight, and age. It uses a true zero, which aids in the representation of intervals between variables by not recognizing negative numbers.
Finally, an article by the Research Prospect states since ratio scales have an absolute zero, variables in this type of data can be added, subtracted, multiplied, or divided (Ingram, 2023). The fact that the variables used in a ratio measurement can be added, subtracted, or divided provides a more analytical approach to a study, and thus making it the most detailed measurement level there is. For these reasons, and many more, it is my level of measurement of choice for conducting a quantitate research.
References:
Williams, K. (2022). Ratio scale: Definition, characteristics & examples. SurveySparrow. https://surveysparrow.com/blog/ratio-scale/
Ingram, O. (2023). Ratio Data: Definition, examples, and analysis. Research Prospect. https://www.researchprospect.com/ratio-data-defini…