How far is Validity of Research Reliable?

Research and analysis is a part of daily routine in laboratories and manufacturing industries across the world. Be it an electronic gadget, medicine, food, cloth or ammunition is subjected to vigorous research and analysis. The results are analysis are checked and evaluated for validity after at-least two trials of analysis. The results of research are expressed as either accurate or precise. Accurate is the exactness of the result and is equal or matches with the theoretical prediction. It is impossible and impractical to give an accurate analysis. Precision is the nearest possible result towards the accuracy. This is evaluated and confirmed after series of results are obtained such that they are very near to accuracy. So in the first instance itself the validity has some sort of questions? 🙂

# research validity

Then the research analysis has many steps, methods with chances of errors  and mistakes. These can be seen as errors in sampling, handling, intermediates, requirements, set conditions and also the final calculations.

1 Sampling: When doing an analysis, samples of the compound are taken in a defined manner. But yet there seems some randomness and chances of some missing of the actual fault samples from analysis. For example, in checking syrups in pharma company, they are taken in defined fashion like every 10 or 10+1 or son from a row. Though sampling is without bias, yet there are chances of missing bottles with deranged packing or labeling or content inside itself.

2. Handling: This part of error occurs due to human or machine handling of samples. When samples are handled there are chances like spillage, contamination from hand itself or incomplete transfer from bottle to beaker etc. Here the reliability of handling depends on experience, concentration, patience, number f samples etc.

3. Intermediates: During a test of a compound, the compound may undergo some reaction with intermediate forms. These intermediates itself can be a interfering with the outcome of data.

4. Requirements: During analysis, there are many reagents, glass ware etc used. These have certain fixed quality or standards.  Change in the quality of these reagents or requirements can sometimes drastically alter the end result.

5. Set conditions: Analysis is done in set conditions of temperature, humidity, time of the day etc.  The set conditions are not same for all the samples and may change leading to variation in data outcome.

6.Calculations: This is a big chance for manipulation. We rely mostly on statistics for interpretation and validity of data. In stats we rely on probability and frequency. Statistics don’t give exact value but instead gives most probable value or data of the analysis. There are many who believe statistics are not accurate and are cause of many errors in validity of analysis. The above opinion is just a thought a personal thought….. Hope it doesn’t affect others view or opinion.. Thanks…

 

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