For good scientific practice, the study design and intended statistical analysis methodology should be laid out even before data collection so that results aren't 'mined' from the data after the study has been conducted. In short, how exactly were the data collected and what are the strong points and limitations of the method?
The type of statistical methodology used will hinge on key assumptions made and ways around limitations of the data. The method may assume a particular model for the data, classically the Normal distribution, or may be a non-parametric analysis, necessarily if the data a qualitative as opposed to quantitative. There may be an assumption about common variance across strata in the data, or other assumed instances of shared parameters that reduce the dimensionality of the model.
The parameters of interest must be clearly identified and ways of maximising the statistical power to estimate them should be addressed carefully.
This would usually be implicit given the outline and description of the models and analysis methods used. Lastly, there may unavoidable biases in the data, such as potential missing data. If the missingness is not at random particular care needs to be taken with this in analysis. Also, the quality of the collected data may strongly affect the usefulness of the findings of the study.
Even if there are large amounts of data, if it is of poor quality it is useless for making informed statements about the phenomenon of interest. Always with the statistical method chosen, there is a trade-off to be made regarding simplicity and interpretability of the model versus accuracy of results, and of power to detect true effects versus controlling type I error finding seemingly interesting effects by pure chance. Time and resources also govern how much data can be collected and the depth and sophistication of the experiment.
To warrant spending a lot of money and time on the research, the outcomes need to be of sufficient interest to the scientific community or private companies and hopefully the general public too and the researchers demonstrate enough confidence regarding the findings they expect to record.
If the right people cannot be convinced that the research deserves time and money it won't go ahead, so conveying the importance of the hypothesis and engendering confidence in the success of the statistical methodology to be used and its worthiness to demonstrate real findings is key.
No matter how convinced the research group is of their ideas, they must convey this effectively to others for the research to be noticed and recognised.
There are scientific standards, and these need to be observed for findings to have credence. I assume that you are asking about the term "nature of the study" with regard to something like the writing of a dissertation.
It suggests to the research person to follow four basic rules, which are specified below. The concept of the research process involves seeing dialogue as a specific form of dialectic. An integrated part of the methodology is its verification procedure with tests of validity, reliability and range of findings. Qualitative heuristics are applicable to all topics within psychology and the human and social sciences which are open to empirical research.
Qualitative data are specially suitable to discover qualitative relations such as structure or patterns and structural changes. We will present an example which shows the systematic exploration and rediscovery of a long-omitted method in psychological research: Explorative methods also have been used extensively within certain branches of psychology e.
There are close associations between qualitative heuristics and classical cultural anthropology and ethnography DAMMANN as well as ethnomethodology but qualitative heuristics in its present form use a wider reservoir of methods and a more comprehensive methodology. Explorative methods and procedures—particularly systematic observations and experiments—have been basic for discoveries within the sciences for centuries, but have been repelled from "Geisteswissenschaften" by DILTHEY and Neo-Kantianism in favor of hermeneutics, and from mainstream psychology and sociology by Behaviorism and Deductionism in favor of measurement along predefined variables.
The first two rules refer to the interaction of the research person and research topic; the second pair to the relationship of the data collection and data analysis. All rules are mutually dependent on each other. This seems to be a rather simple rule and easy to follow, but it is not. The scientific identity of researchers largely depends on the confirmation of basic beliefs about the research process and the nature of the topics under study. Alas, discoveries in many cases contradict general scientific beliefs which are hard to give up and may even cause crises within the process of research itself.
The rule suggests a reconsideration of the researcher's scientific position if the data consistently are not in agreement with information taken for granted. In science such "paradoxes" have become prominent starting points for exploration MACH , pp. The topic of research is preliminary and may change during the research process. It is only fully known after being successfully explored.
The topic may be overlapped by another one or turn out as part of a different problem or just disappear as ether in physics, status inconsistency in sociology or the location of the soul in psychology—even soul itself, though neuroscience raises the question again.
If this happens the research person is advised to continue the research under new headings despite institutional and planning problems that may arise. Changes of this sort should be regarded as a positive sign of accumulation of knowledge. There are famous examples of findings despite opposing definitions—i.
Data should be collected under the paradigm of maximum structural variation of perspectives. Variation of the sample and of research methods avoid one-sidedness of representation of the topic, variation of questions avoid just one answer.
If researchers assume that a variable may influence the data they should implement variations. Structural variations mean sampling of positions in reference to the topic, i. The kind of variation will always depend on the theme under study. The analysis is directed toward discovery of similarities. It locates similarities, accordance, analogies or homologies within these most diverse and varied data.
It tries to overcome differences. The rule follows SIMMEL's famous chapter on method saying that "out of complex phenomena the homogeneous will be extracted The analyst starts grouping those parts of the protocols or observations which are most similar to other parts and continues to group the groups tentatively, suggesting headlines for the groups and then headlines on top of headlines thus progressing from concrete parts to a more and more abstract general whole which nonetheless keeps concrete details.
Proceeding in this manner, the overall pattern, showing the structure of the topic, will gradually emerge. The analysis is integrated into the process of data collection and mutually dependent on it.
Research procedures are not linear but dialectical. We "ask" our material "questions" in a similar way one may ask a person, receiving "answers" and questioning again.
We preferably use "open" questions. Reading a protocol will suggest which questions to ask. The text should be interrogated from as many different perspectives as possible and the answers analyzed as mentioned above.
The dialogic procedure is a means to adjust the epistemic structure of the researcher to the structure of the phenomenon and brings it in line with itself "Anpassung der Gedanken an die Tatsachen und aneinander", MACH , pp. An analysis which has been performed successfully will test itself "inner validity". It is valid in case new variations of data and perspectives will not bring new results but confirm the existing ones.
In addition "testing the limits" of the analysis will show the range within which results are valid. All research findings as all phenomena in the Humanities are historical which means they are subject to change, whether referring to individuals, groups or societal organizations.
Nature and Scope of Research Methodology. It is an art of scientific investigation. mihtorg.ga Is Research? RESEARCH is the systematic collection.. and at last carefully testing the conclusions to determine whether they fit the formulating hypothesis. collecting/5(8).
Chapter – 1 Nature, Scope, Objectives and Methodology of Research Introduction Significance of the Study Scope of the Study Objectives of the Study.
Types of research methods can be classified into several categories according to the nature and purpose of the study and other attributes. In methodology chapter of your dissertation, you are expected to specify and discuss the type of your research according to the following classifications. The Nature of Research. The research process is, for many of us, just the way we do things. We research the best buys in cars and appliances, we research book reviews before shopping for books, we research the best schools for our children and ourselves, and we .
The methodology provide basic plans for the research activity which is closely related with aspects such as the type of research problem, the formulation of research questions, the methodological concerns, the type of data gathered, and the method of data analysis (Cohen et al., )/5(5). Research Methodology - Introduction - Meaning and objectives of research, Research V/S Research methodology, Research Process, Features of a Good Research.