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Methods CASE5 - Research Paper Example

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Such researches study the numerically classified components of a study group. The numerical composition and computation of such research results allow for easy analysis. The research results are categorized…
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Research Methods CASE5
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Research Methods CASE5 Quantitative research analyses the measurable components of a Such researches study the numerically classified components of a study group. The numerical composition and computation of such research results allow for easy analysis. The research results are categorized statistically in relational mechanism with one component of the variable showing a relation with the other. The statistical display of results allows for analysis of the result using such formulas as the t test analysis (David, 2005). This is statistical tool used only if the result supports a null hypothesis. It is most commonly applied if the statistical result of the research follows a normal distribution. Additionally its usage is only applicable when the scaling term of the data is known. Incase this is unknown, it is advisable to replace the term with an estimate from the data thereby making t test computation possible (Yule,1897).
Analysis of variance or ANOVA on the other hand is a statistical tool used to analyzed research finding that uses the process of partitioning the research variance into components attributable to various sources. This tool provides a statistical test used to determine whether or not the means of a number of groups are all equal. In doing this, this analysis tool generalizes t-test to more than two groups in a particular research. A qualitative research unlike a quantitative one bases its study on the analysis of qualitative phenomenon of the research subjects. Such studies are concerned with the subjective assessments of attitudes, opinions and behaviors of a research group. Regression analysis is the best tool used in analyzing the research findings of a qualitative research (Kutner, Nachtsheim &Neter, 2004). This tool clearly displays the relationship between two or more variables. If effectively used the tool clearly depicts the relationship between dependent and independent variables in a study.
References
David A. F. (2005). Statistical Models: Theory and Practice. Cambridge: Cambridge University Press.
Kutner, M. Nachtsheim, C. &Neter, J. (2004). Applied Linear Regression Models. New York: McGraw-Hill/Irwin, Boston
Yule, G. (1897). On the Theory of Correlation: Royal Statist. New York: Blackwell Publishing. Read More
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