Differences between measurement and observation
Observation relates to a situation where a researcher is interested in the traits of the participants involved in the study. In such a scenario, a researcher can decide to interact with participants and become part of them so as to understand their behavior. Apart from interacting with the participants, a researcher can also decide to record behavior of participants without interacting with them making it is possible to analyze the characteristics of the participants. For example, a researcher could be interested in identifying the traits among university students on their preferred refreshment brands. To record the observations, the researcher could position themselves in a retail store at the institution and record the different types of drinks bought by the students. Measurement, on the other hand, implies use of various scales of measure to provide estimates of relationship among variables in a study. Measurable scales are ordinarily used in situations where a researcher is interested in obtaining differences in age among students to make a statistical decision.
Nominal, ordinal, interval and ratio measurements
Ordinal measurements involve ranking of cases in order to reflect more or less of an attribute. However, the ordinal measurement scale does not involve measurement of how much or less a variable is. This implies that the ordinal scale only interprets the order without description of distances in the variables. An example of application of ordinal scale is assigning students’ performance into categories such that there is excellent, good, average and poor performance among students. Ratio scales are used to estimate the extent of magnitude of continuous quantities of variables. The variables that could be used as ration scales include; length, time, mass and angles. Nominal scale involve placing of data into categories without the need for a particular order or structure. An example of a nominal scale is a yes or no response such that there is no order or distance between the two responses. The variables to be used for the nominal scales are no-parametric and hence require no numerical estimation of relationships among variables. Interval scale is used in the case where there are equidistant points between variables. Through reliance on interval scales, it is possible to interpret the differences in the distance along the scale.
Importance of knowing the levels of measurement for variables
Levels of measurement are key to identifying the relationship among values assigned to the attributes of a variable. This then makes it easier to interpret the data from the variables used in a survey. Levels of measurements are also significant in enabling a data analyst to decide the most suitable statistical analysis on the values assigned. For instance, in case where there are nominal scales used, an analyst is able to acknowledge that t-test cannot be applied in the analysis stage.
Techniques used to improve the validity and reliability of variable measurements
Various techniques are used to improve the validity and reliability of variable measurements so as to ensure that the findings can be used for future research and policy implementation. Such techniques include triangulation which involves collection of data through different sources, including questionnaires, interviews and observations to eliminate incidences of questionable, weak and biased data. Relying on peer reviews is also important since it enhances ability to review previous research data findings to be able to validate the reliability of variables used for a study. Long term observation is also a key technique that can be used to improve reliability and validity of variables since repeated observations are made for a longer period of time. From the extended duration of observation, it is then possible to identify the suitability of the variables used for a study. Participants could be used to confirm reliability of the findings such that findings by simply having the results sent back to the participants to confirm and validate the variables used in a study.
Works Cited
Driscoll, Dana. Introduction to Primary Research: Observations, Surveys, and Interviews. New York: Pavel, 2011. Document.
Fife-Schaw, Chris. Levels of Measurement. New York: Breakwell, 2006. Document.
Golafshani, Nahid. "Understanding Reliability and Validity in Qualitative Research." The Qualitative Report (2003): 597-607. Document.
Zohrabi, Mohammad. "Mixed Method Research: Instruments, Validity, Reliability and Reporting Findings." Theory and Practice in Language Studies (2013): 254-262. Document.
