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 quantitative …show more content…
Therefore, discrete variables have the potential of being used precisely and without error; and although counting errors could still occur, precise measurement is possible. An example of a discrete variable could be family size, since even though this would include a wide range of possible values, it would still be able to be counted as separate units. Another example would be a test that utilizes true or false questions, an answer can be either one or the other, but not anything in between. Nonparametric statistics from tests would correspond with discrete variables, since these types of tests do not require a numerical score (Gravetter & Walnau, 2014). Therefore, discrete variables would normally use nominal or ordinal
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 quantitative …show more content…
Therefore, discrete variables have the potential of being used precisely and without error; and although counting errors could still occur, precise measurement is possible. An example of a discrete variable could be family size, since even though this would include a wide range of possible values, it would still be able to be counted as separate units. Another example would be a test that utilizes true or false questions, an answer can be either one or the other, but not anything in between. Nonparametric statistics from tests would correspond with discrete variables, since these types of tests do not require a numerical score (Gravetter & Walnau, 2014). Therefore, discrete variables would normally use nominal or ordinal