It is true that measurements are meant to provide high-quality data that is error-free which would aid in the testing of hypotheses and in making of estimations. When presenting data one may utilize different classification measurement scales. The four main scales used include the nominal, ordinal, interval and ratio scales. The scales slightly differ in information collection and illustration.
In utilizing the ratio scale in illustrating the data of the annual salary of 200 employees working in a corporation one may use various empirical approaches. This is because in addition to the provision of an absolute zero origin ratio scales possess the qualities of the other three data presentation methods. Information presented in the ratio scale may be such as the gender of the employees, the range of their salaries, the number of years they have worked for the organization and their job satisfaction level. Interval scales are forms of data that indicate the difference in values between two quantified measures. In addition to the concept of equality intervals, the measure has the measure qualities of nominal and ordinal data (Cooper & Schindler, 2014, p.253). In utilizing interval scales to collect data the organization may incorporate ranges to determine employee satisfaction levels. This data would assist in evaluating how salary range, gender, and the number of employment years have contributed to the employees' satisfaction levels.
The ordinal scale involves the use of different classification measures to describe the nature of information obtained (Han et. al, 2011, p42). In addition to the characteristic element, ordinal scales have nominal scale features. In the corporation's case, the ordinal scale can be utilized in determining how satisfied the employees are with their salaries in consideration of their gender differences. Nominal scales usually have variables with ordered categorical scales (Agresti, 2010, p1). Nominal scales can be used in collecting data from variables which can be grouped to mutually exclusive and collectively exhaustive data. In the case presented this presentation method can be used in determining how many men and women forms the company's population of 200 employees.
It is true that pieces of data are being lost as the scale moves from ratio to nominal scale thus reducing the amount of information that can be gathered from the data. The loss of information has been mainly caused by the progressive reduction in the amount of information being gathered. The student has managed to effectively show how the data can be presented through the four methods of data presentation. The student's use of similar measures that have been progressively faced out has allowed easy understanding of the difference in quantity and quality of information that can be obtained from the four different methods. However, by describing the importance of each presentation method the student would show where each method can be most suitably utilized.
The words from Proverbs 2:2 turn your ears to wisdom and apply your heart to understanding,' would encourage the management team to utilize information gathering methods that ensure they fully understand their employees. This is because through understanding they would be able to know how they can motivate their employees to work even harder thus benefiting themselves and the organization.
Agresti, A. (2010). Analysis of ordinal categorical data (Vol. 656). John Wiley & Sons.Cooper, D. R., & Schindler, P. S. (2014). Business research methods (12th ed.). New York, NY: McGraw-Hill.
Han, J., Pei, J., & Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.
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