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Generating Hypotheses and Building Theories - Essay Example

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In the paper “Generating Hypotheses and Building Theories” the author explains data usage both in testing hypotheses and theories and in generating hypotheses and building theories. Theory testing and theory building are two different ways through which researchers undertake their research studies…
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Generating Hypotheses and Building Theories
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For instance, a researcher studying the cause of global warming may consider testing the Anthropogenic Global Warming (AGW) theory. The rationale behind testing such a theory is to uncover whether the AGW theory best explains global warming. Therefore, the researcher may test the theory by looking at the humidity levels resulting from the emission of carbon dioxide. Theory testing aims at collecting evidence to either confirm or contest a theory. In theory building, the researcher synthesis literature content related to his or her interesting topic of study in an attempt to explain a given phenomenon.

For instance, a researcher studying the concept of global warming may consider the analysis of all theories related to global warming including the AGW theory (Polkinghorne, 2005). The usage of data in testing already constructed hypotheses and theories is advantageous since the analysis that shall be done is meant to confirm or dispute the given theories and hypotheses. On the downside, this statistical method is prone to the aligning of new information to old findings and may thus eliminate other findings not taken care of by the theory or hypothesis in question (Leedy & Ormrod, 2010).

On the other hand, the usage of data in generating hypotheses and building theories has its advantages among them the completeness and depth of analysis and drawing of conclusions (Johnson & Onwuegbuzie, 2004). This is due to the fact that there are no biases the researcher is exposed to (Polkinghorne, 2005). The disadvantage is that the conclusions are exposed to many untested results.Q2. Two Rationales for Using Mixed Data ApproachThe first rationale for employing the mixed data approach, which harnesses both qualitative and quantitative research techniques, is that it enables the researcher to eliminate the confounding influence of many variables with the advantage of a clear assessment of the relationship between causes and effects.

This is due to the fact that each variable is well-dealt with owing to there being enough techniques to deal with each variable in detail. The second rationale for the use of the mixed data approach is that it avails many useful tools available in one data approach and lacking in the other with the result that rigorous and precise conclusions are made owing to the depth of the research (Christensen, Johnson & Turner, 2011). Researchers consider the use of mixed research methods because of its ability to incorporate data collection techniques used under qualitative and quantitative research.

Therefore, a mixed research method enables a researcher to use highly structured numerical surveys in collecting data from a large sample population. Additionally, a mixed research method can also include data from a smaller population. The end result is that a researcher is able to refine, extend, and explain specific findings such as relationships and differences among participants. Additionally, the researcher can explain any results that are unexpected using the words of the participants.

The benefit to the researcher here is that the results obtained are treated with more validity.

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