data levels of measurements for quantitative data
Quantitative data is defined as the value of data that is identified numerically in numbers and counts where every data-set is recognized to have a unique numerical value that is in association (Abulela and Harwell, 2020). Quantitative data can be quantifiable, and the information is primarily used for statistical analysis to make real-life decisions based on developed mathematical derivation. Some of the popular questions that are answered by the use of quantitative data re how often? How many? How much? Qualitative data is primarily collected by the use of questionnaires, surveys, and polls on an identified population. There are four data levels of measurements for quantitative data. Researchers pick on their preferred level of measurement for the data based on the available data for analysis.
The nominal level of measurement is the first level of measurement on quantitative data. In this level of measures, researchers are allowed to use letter words and alpha-numeric symbols to undertake the analysis (Vinik et al., 2016). In this level of measurements, values that are often identified are out layers such as an individual not belonging to either male or female is classified as a third category. Ordinary level of measurement is preferred to use an ordered relationship among the observed variables. For example, in a marathon race, the winner is classified as number one about the race scores. Then for the last runner is classified as last compared to the rank. Thus, in this measurement, level ranks are observed based on estimations.
The Interval level of measurements is the third classification that gives classification based on the specific variations between every interval on the scale (Puzi, Sidek, Rosly, Daud, and Yuso, 2017). Therefore, there is no relationship between the first values to the second; there is a possibility to have a high-value interval in one verse the subsequent entry-level. The ratio level of measurement is based on observations that are conducted by the researcher then opts to have equal intervals between one variable to another. In this measurement, value zero is considered, unlike other measurements. In this level of analysis, the divisions that are in existence between the points of scale are noted to be equivalent to help the researcher develop and observe a pattern. The ratio level measurement gives exact values.