Qualitative And Nonparametric Statistics

902 Words 4 Pages
This paper will seek to explain the difference between quantitative and qualitative data, as well as how quantitative data can be collected using continuous and discrete variables. Parametric and nonparametric statistics will be discussed in relation to different variables, and how they can be used to analyze collected data. Examples connected to personality testing will be given and related to possible best uses for various types of information and data. Additional information may be presented as it applies to various concepts or the topics discussed.
Variables
The primary methods of research can be categorized as quantitative or qualitative, and both can be used to answer questions in the behavioral sciences, such as psychology. Each one is different in how assessment and data gathering is done, and each involves a different realm of inquiry. Quantitative data is information obtained through measurement and relayed via numerical form (Smith, 2015). Qualitative data are usually displayed through descriptions, rather than numbers, and is therefore more difficult to measure or analyze than
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Personality is a continuous variable which differs from one person to another. Using a test such as the MBTI makes nonparametric statistics usable by considering only discrete variables, but does so at the cost of accuracy. On the other hand, the NEO-PI tries to capture as much information as possible and converts it into numerical form, which allows for a greater amount of statistical operations to be performed. However, in terms of development or team building, the use of discrete variables may give simpler and more tangible information, as seen with the MBTI. Ultimately though, the NEO-PI, or similar tests which use continuous variables and parametric statistics, would give a better indication of an individual’s personality for situations such as employee

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