Whichever reasoning processes and research methods were used, the final conclusion is critical, determining success or failure. If an otherwise excellent experiment is summarized by a weak conclusion, the results will not be taken seriously.
Success or failure is not a measure of whether a hypothesis is accepted or refuted, because both results still advance scientific knowledge.
Failure is poor experimental design, or flaws in the reasoning processes, which invalidate the results. As long as the research process is robust and well designed, then the findings are sound, and the process of drawing conclusions begins.
The key is to establish what the results mean. How are they applied to the world?
What Has Been Learned
Generally, a researcher will summarize what they believe has been learned from the research, and will try to assess the strength of the hypothesis.
Even if the null hypothesis is accepted, a strong conclusion will analyze why the results were not as predicted.
In observational research, with no hypothesis, the researcher will analyze the findings, and establish if any valuable new information has been uncovered.
Generating Leads for Future Research
However, very few experiments give clear-cut results, and most research uncovers more questions than answers.
The researcher can use these to suggest interesting directions for further study. If, for example, the null hypothesis was accepted, there may still have been trends apparent within the results. These could form the basis of further study, or experimental refinement and redesign.
Evaluation - Flaws in the Research Process
The researcher will then evaluate any apparent problems with the experiment. This involves critically evaluating any weaknesses and errors in the design, which may have influenced the results.
Even strict, 'true experimental,' designs have to make compromises, and the researcher must be thorough in pointing these out, justifying the methodology and reasoning.
For example, when drawing conclusions, the researcher may think that another causal effect influenced the results, and that this variable was not eliminated during the experimental process. A refined version of the experiment may help to achieve better results, if the new effect is included in the design process.
In the global warming example, the researcher might establish that carbon dioxide emission alone cannot be responsible for global warming. They may decide that another effect is contributing, so propose that methane may also be a factor in global warming. A new study would incorporate methane into the model.
What are the Clear-Cut Benefits of the Research
The next stage is to evaluate the advantages and benefits of the research.
In medicine and psychology, for example, the results may throw out a new way of treating a medical problem, so the advantages are obvious.
However, all well constructed research is useful, even if it is just adding to the fount of human knowledge. An accepted null hypothesis has an important meaning to science.
Suggestions Based Upon the Conclusions
The final stage is the researcher's recommendations based upon the results, depending upon the field of study. This area of the research process can be based around the researcher's personal opinion, and will integrate previous studies.
For example, a researcher into schizophrenia may recommend a more effective treatment. A physicist might postulate that our picture of the structure of the atom should be changed. A researcher could make suggestions for refinement of the experimental design, or highlight interesting areas for further study. This final piece of the paper is the most critical, and pulls together all of the findings.