Execution of Project Through Generalization and Interpretation

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Execution of the project:
Execution of the project (implementation phase of the project) proceeds on correct lines, the data to be collected would be adequate and dependable. The researcher should see that the project is executed in a systematic manner and in time. If the survey is to be conducted by structured questionnaires, data can be readily machine-processed. In such situation, questions as well as the possible answers may be coded. If the data are to be collected through interviewers, arrangements should be made for proper selection and training of the interviewers. Steps should be taken to ensure that the survey is under statistical control, so that the collected information is in accordance with the pre-defined standard of accuracy.

It is the responsibility of the researcher to provide evidence regarding the reliability, validity and generalizability of the findings. The report should clearly identify the target population to which the findings apply. Factors that limit the generalizability of the findings, such as the nature and representativeness of the sample, mode and time of data collection, and various sources of error should be clearly identified. The reader should not attempt to generalize the findings of the report without explicit consideration of these factors.

Interpretation and Conclusions:
The findings should be reported in an objective and candid way. The interpretation of the basic results should be differentiated from the results parse. Any assumptions made in interpreting the results should be clearly identified. The limitations of the research should be discussed. Any conclusions or recommendations made without a specification of the underlying assumptions or limitations should be treated cautiously by the reader.


Generalization is to which extent the research and the conclusions of the research apply to the real world. It is not always so that good research will reflect the real world, since we can only measure a small portion of the population at a time. In fact every research study, somehow tries to relate observations to theory. If a hypothesis is tested repeatedly then researcher can move to generalization and construct a theory out of it. This is the real objective of the research.


Generalization identifies commonalities among a set of entities. The commonality may be of attributes, behavior, or both. For example, a statement such as "All windows have a title" expresses a common attribute among all entities that are considered windows. Similarly, the statement, "All windows can be resized." expresses a common behavior that all windows provide. Generalizations are usually easy to recognize as they contain words like "all" and "every".

Generalization is an essential component of the wider scientific process. In an ideal world, to test a hypothesis, you would sample an entire population. By Martyn Shuttleworth (2008)

You would use every possible variation of an independent variable. In the vast majority of cases, this is not feasible, so a representative group is chosen to reflect the whole population.

For any experiment, you may be criticized for your generalizations about sample, time and size.

•You must ensure that the sample group is as truly representative of the whole population as possible.

•For many experiments, time is critical as the behaviors can change yearly, monthly or even by the hour.

•The size of the group must allow the statistics to be safely extrapolated to an entire population.

In reality, it is not possible to sample the whole population, due to budget, time and feasibility. For example, you may want to test a hypothesis about the effect of an educational program on schoolchildren in the US.

For the perfect experiment, you would test every single child using the program, against a control group. If this number runs into the millions, this may not be possible...
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