This is yet another reason we cannot assume that data is 'objective' because it is quantitative in nature. For example, when constructing an experiment "an extreme groups design (e.g., assigning participants to high or low conditions) maximizes the variances of the components of the product term, it also results in much more power with respect to the interaction effect than would the corresponding observational design" (Cortina 2002: 343). Conversely, doing an experiment 'in the field' is likely to yield a less statistically-significant impact because of the inability to control the extremity of the variables. A recent study of the statistical power of research in the social sciences revealed that only 40% of all MIS studies had adequate statistical power to ensure that the probability that the null hypothesis would be rejected correctly at all times (Baroudi & Orlikowski 1989: 87). Significance criteria, sample estimate, and effect size, can all influence statistical power and once again, when dealing with human subjects, many additional variables can affect statistical power (Baroudi & Orlikowski 1989: 87).
The use of certain statistical conventions can also yield inaccurate results, if deployed in an inappropriate fashion. For example, disregarding 'outliers' or extremes that impact the findings is a common practice and may be appropriate or inappropriate, depending upon the circumstances, as can filling in missing results to enable the statistical analysis to be done in the first place (Gardenier & Resnik 2002: 68). If the outliers are not genuine 'outliers' that can be explained convincingly as such or the missing data cannot be extrapolated easily, it can produce wildly inaccurate results.
Sometimes the misuse of quantitative data is unintentional, other times it is deliberate. In some instances, data may be obtained in a fraudulent and unethical manner, deliberately designed to produce a particular, false result (such as editing, cleaning, or mining data) or aspects of...
Today, social science researchers have a wide range of research methods available for criminology and criminal justice applications, divided generally between quantitative and qualitative methods. Although quantitative and qualitative research methods share some commonalities with respect to their overarching objectives, there are some fundamental differences involved that must be taken into account when selecting an optimal research strategy for a given research enterprise. The purpose of this paper was to
Construct a Research Design Using Secondary Data Part 1 Secondary data takes into account data that is gathered by someone else aside from the user. Examples of sources of secondary data comprise of data gathered by government establishments, organizational records in addition to data that was initially gathered for other purposes of research. The secondary data selected for this paper is census. In delineation, a census is the process of methodically obtaining
Strengths/Weaknesses of the Quantitative ApproachIntroductionQuantitative research is a widely used approach in public administration research that involves the collection and analysis of numerical data. This approach has several strengths, including the ability to use probability sampling methods to select representative samples, the ability to replicate studies to verify findings, and the ability to collect large amounts of data quickly and efficiently. However, there are also limitations to quantitative research, such
Quantitative vs. Qualitative Research According to Lopez-Alvarado (2017) and Muijs (n.d.), research design decisions are linked to ontology and epistemology. Ontology refers to the researcher’s beliefs about whether reality is absolute or contextual, universal or relative. Whether the researcher is a realist or a relativist determines research questions and designs, with an increased tendency for relativists to focus on phenomenological and qualitative methods and a realist to use quantitative methods. Muijs
Methods Preferring to use a quantitative approach to provide the business community with numerical data it can use to transform organizational practices and increase employee retention, I will be using a survey as the primary instrument of data collection. Pennsylvania State University (2006) defines a survey as “a research method for collecting information from a selected group of people using standardized questionnaires or interviews,” (p. 1). While the central component of
Both qualitative and quantitative research methods have the potential to yield reliable, valid, and important information that can be used to inform public policy. Criminal justice researchers use a wide range of research methods, which vary depending on the research questions, the purpose of the study (applied versus pure research) and the overall paradigm and theoretical framework. Research can be used to validate or disprove an existing theory, alter or
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