Measuring Variables
Differences between Measurement and Observation
Observation and measurement research are classified as the major investigation types in regard to research. The primary distinction amid the two lies on the manner in which scrutiny is conducted. In regard to measurement, the researcher normally engages in several experiments without making any kind of observations on the other hand observation involves making direct observations in order to develop an informed conclusion (Bachman & Schutt, 2017). On other words, observation includes all that can be observed. In regard to measurements, the researcher has the capability of manipulating all the aspects in regard to developing conclusions. However, in observational research experiments are conducted and the researcher mainly depends on the gathered information’s (Benz & Newman, 2008). In regard to measurements, observations are made via different evaluations.
Dissimilarities amid the Four Heights of Measurement
Nominal measurement mainly depends on categories and labels. In this context, the collected data at the nominal stage is usually qualitative. Given that the collected data in this context cannot be evaluated or organized in a useful way and therefore, there is no reason in calculating the associated subjects such as standard deviations (Benz & Newman, 2008). On the other hand, ordinal measurement implies that at this level it is easier to organize data but the distinctions about information are not very useful. Both in the nominal and the ordinary stage data should not be utilized for calculations. This differs with interval measurement that is mainly grounded on organized data and the distinctions amid the acquired information is treated as important given that it offers reasonability (Bachman & Schutt, 2017). However, at this stage data is not characterized by any central point. This implies that within the level data can be utilized in regard to calculations, however comparing the data is not associated with any kind of assessment (Benz & Newman, 2008). Ration measurement is the highest measurement stage and in this context, data is utilized in developing conclusions (Benz & Newman, 2008). The acquired data can be separated to develop an organized structure.
The Importance of Understanding Measurement Levels In Relation To Study Variables
Measurement levels can best be described as the association amid the assigned values to the variable features. First, understanding the measurement height is useful in deciding the manner in which the acquired information can be interpreted (Bachman & Schutt, 2017). Understanding that the procedures are nominal helps to interpret the general implication of the unorganized data. In addition, understanding the measurement height assist in making decisions in regard to the statistical evaluation to utilize that suits the set concepts (Bachman & Schutt, 2017). More so, this helps in establishing the actual implication of the data.
Techniques Can Be Utilized To Improve the Validity and Reliability of Variable Measurement
Reliability can be utilized to refer to the dependability of information. On the other hand, validity is the rationality acquired from any given information (Withrow, 2013). This, therefore, implies that both cannot be acquired without the availability of consistency. In improving rationality and reliability there are several strategies that can be applied which in turn improves the general accuracy of the investigation. First controlled examinations can be utilized in controlling the general association amid the performed investigation. In addition, sample sizes can be utilized in ensuring that the study does not divert from the set objective (Withrow, 2013). This helps in setting a straight direction which in turn develops dependable and precise conclusions that are relevant to the subject.
References
Benz, C. R., & Newman, I. (2008). Mixed methods research: Exploring the interactive continuum. Carbondale: Southern Illinois University Press.
Bachman, R., & Schutt, R. K. (2017). The practice of research in criminology and criminal justice (6th Ed.). Thousand Oaks, CA: Sage.
Brian L. Withrow. (2013). Research Methods in Crime and Justice. Rutledge.
