importance of quantitative research in information and communication technology
Harper and Row. Deduction is a form of logical reasoning that involves deriving arguments as logical consequences of a set of more general premises. The study was conducted at the Institute of Accountancy Arusha (IAA) involving IT academic staff with at least one IT professional certification. The whole point is justifying what was done, not who did it. (2013). The American Statistician, 60(4), 328-331. So if either the posited independent variable or the confound (a rival variable) is poorly measured, then you cannot know with any certainty whether one or the other variable is the true cause. Interpretive researchers generally attempt to understand phenomena through the meanings that people assign to them. Cronbach, L. J. Beyond Significance Testing: Statistics Reform in the Behavioral Sciences (2nd ed.). Burton-Jones, A., & Lee, A. S. (2017). Selection bias means that individuals, groups, or other data has been collected without achieving proper randomization, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. Unfortunately, unbeknownst to you, the model you specify is wrong (in the sense that the model may omit common antecedents to both the independent and the dependent variables, or that it exhibits endogeneity concerns). Induction and introspection are important, but only as a highway toward creating a scientific theory. If the data or phenomenon concerns changes over time, an analysis technique is required that allows modeling differences in data over time. The omega test has been made available in recent versions of SPSS; it is also available in other statistical software packages. It stood for garbage in, garbage out. It meant that if the data being used for a computer program were of poor, unacceptable quality, then the output report was just as deficient. 571-586. WebThe purpose of this action research was to explore the information and communication technology (ICT) literacy skills of first-year minority students at Saint Augustine's Journal of Socio-Economics, 33(5), 587-606. (2019). Communications of the Association for Information Systems, 20(22), 322-345. During more modern times, Henri de Saint-Simon (17601825), Pierre-Simon Laplace (17491827), Auguste Comte (17981857), and mile Durkheim (18581917) were among a large group of intellectuals whose basic thinking was along the lines that science could uncover the truths of a difficult-to-see reality that is offered to us by the natural world. An example would be the correlation between salary increases and job satisfaction. (2017). If your instrumentation is not acceptable at a minimal level, then the findings from the study will be perfectly meaningless. Data that was already collected for some other purpose is called secondary data. Journal of Marketing Research, 18(1), 39-50. MIS Quarterly, 13(2), 147-169. Journal of Personality Assessment, 80(1), 99-103. Too Big to Fail: Large Samples and the p-Value Problem. (2010) suggest that confirmatory studies are those seeking to test (i.e., estimating and confirming) a prespecified relationship, whereas exploratory studies are those that define possible relationships in only the most general form and then allow multivariate techniques to search for non-zero or significant (practically or statistically) relationships. Explained variance describes the percent of the total variance (as the sum of squares of the residuals if one were to assume that the best predictor of the expected value of the dependent variable is its average) that is explained by the model variance (as the sum of squares of the residuals if one were to assume that the best predictor of the expected value of the dependent variable is the regression formula). Popper, K. R. (1959). This is because experimental research relies on very strong theory to guide construct definition, hypothesis specification, treatment design, and analysis. This post-positivist epistemology regards the acquisition of knowledge as a process that is more than mere deduction. It implies that there will be some form of a quantitative representation of the presence of the firm in the marketplace. As the name suggests, quantitative methods tend to specialize in quantities, in the sense that numbers are used to represent values and levels of measured variables that are themselves intended to approximate theoretical constructs. The guidelines consist of three sets of recommendations: two to encourage (should do and could do) and one to discourage (must not do) practices. The Logic of Scientific Discovery. B. Woszczynski (Eds. What matters here is that qualitative research can be positivist (e.g., Yin, 2009; Clark, 1972; Glaser & Strauss, 1967) or interpretive (e.g., Walsham, 1995; Elden & Chisholm, 1993; Gasson, 2004). Organization Science, 22(4), 1105-1120. Educational and Psychological Measurement, 20(1), 37-46. Journal of the Association for Information Systems, 18(10), 727-757. WebThe data for this quantitative research were analyzed for both descriptive and inferential statistic using SPSS (version 21) software. Experimental and Quasi-Experimental Designs for Generalized Causal Inference (2nd ed.). Measurement for the Social Sciences: The C-OAR-SE Method and Why It Must Replace Psychometrics. Other endogeneity tests of note include the Durbin-Wu-Hausman (DWH) test and various alternative tests commonly carried out in econometric studies (Davidson and MacKinnon, 1993). Only that we focus here on those genres that have traditionally been quite common in our field and that we as editors of this resource feel comfortable in writing about. The issue is not whether the delay times are representative of the experience of many people. The ubiquity of the portable document format (PDF) journal articles, the growth of However, critical judgment is important in this process because not all published measurement instruments have in fact been thoroughly developed or validated; moreover, standards and knowledge about measurement instrument development and assessment themselves evolve with time. Different treatments thus constitute different levels or values of the construct that is the independent variable. Behavior Research Methods, 43(3), 679-690. This paper is the first to focus on the academic impact of quantitative research in social work developing measurable outcomes. Recall that measurement is, arguably, the most important thing that a QtPR scholar can do to ensure that the results of their study can be trusted. It results in the captured patterns of respondents to the stimulus presented, a topic on which opinions vary. ), such that no interpretation, judgment, or personal impressions are involved in scoring. What is the importance of quantitative research in geography? Block, J. However, in 1927, German scientist Werner Heisenberg struck down this kind of thinking with his discovery of the uncertainty principle. With canonical analysis the objective is to correlate simultaneously several metric dependent variables and several metric independent variables. 
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