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Quantitative analysis - Research Paper Example

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Quantitative analysis Quantitative research involves collection and analysis of quantitative data. The type of data that the research method involves is objective, contrary to subjective data that researchers encounter in qualitative research. Like qualitative research, quantitative faces a number of challenges in its implementation and this paper evaluates some of the challenges of conducting quantitative research and analyzes the issues associated with sampling, validity, reliability, and bias…
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Quantitative analysis
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Download file to see previous pages History confound defines events that occur during the data collection process to influence the dependent variable without effects from independent variable. The events may increase effects of the independent variable or reduce them and therefore compromises validity of data. Maturation confound however defines transitions in research participants’ cognitive or physical properties towards different rationale by the same person. A longitudinal study may involve change in age that associates with improved rationale and physical characteristics that may change an individual’s perception. Other factors such as education, stress, and physical strain may also influence a person’s rationale into different perspectives during a study. Test confound is another challenge to quantitative research and defines differences in results because of a research participant’s previous experience with the test instrument and the experience influences results from values that would be observed on first encounter with the same test. Interactive effect is another threat to quantitative research and defines association between two or more confounds in a study. Interaction between treatment and history is an example results in different values from actual effects of a study’s independent variables (LoBiondo & Haber, 2013). Challenges of quantitative research are evident and offer a basis for differentiating between quantitative and qualitative research. Their understanding are therefore important, not only for development and implementation of qualitative research initiatives, but also for understanding differences between the two research methods in order to ensure development of a suitable research methodology for a study (Allwood, 2012). History confound is a significant threat to quantitative research because of its potential to alter results in a study. History can occur in a study’s internal or external environment and this defines the extent to which it may be significant to a study. In a study to investigate effects of lecturers’ appearance on effectiveness of learning process, an independent forum on learning skills that averts students’ attention from a lecturer’s appearance is an external historic factor to the study. A seminar to lecturer’s on how to improve their lecturers is however, an external historical factor and both offer significant potential to shifting the relationship between lecture’s appearance and effectiveness of lecturers. The extent of such an impact on results further depends on effectiveness of the history factor. The challenge is based on factors beyond rationale of research participants and therefore defines independence from bias, unless the history event is selective to influence a proportion of research participants and their associated data. In the absence of bias, history has uniform impacts on phenomenon of study and therefore ensures reliability of collected data because of a possible uniform shift in relationships. Consistency in measures will therefore be attained in a historically confounded study but validity will be compromised because of lost accuracy on the effects of independent variables on the subject dependent variable. Possible existence of reliability but not validity in a data ...Download file to see next pagesRead More
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Quantitative Analysis
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