 Today I am going to discuss a very important term with you which is being often discussed in research. You must be aware of the concept of research replicability, but here I am going to discuss the concept which is a little variant than that and it is research reproducibility. Research reproducibility in research is important to validate finding. Now to see what it is actually, reproducibility is defined as when a researcher is able to duplicate the same phenomena even when experimental conditions are varied. The concept is that when there are the same conditions then we can produce the same results after an experiment. But the research reproducibility is different in a way that when your experimental conditions are varied but still the same results can be produced. Replicability is defined as when a researcher is able to obtain the same results when the experiment is conducted under the same experimental conditions. This is something which is a very early lesson for a psychology student that we always talk about replicability and we understand that when there are the same testing conditions then we will be going to achieve the same testing results. Although reproducibility is promoted in science, researchers are not keen to replicate or read published research. It is very important that we talk about replicability, but we have never in true sense reproducibility has no effort in finding published research and we have never searched it and we have never seen the factors that come in the form of a research that comes in the form of replicability then we can study it as a section of reproducibility that either there are such confounding variables that we can reproduce that research even because of controlling it. Moreover, the published research work is expected to be reproducible but it is really tested on the other grounds later. Like there are some very tried and testing phenomena, if we try them on different norms then their reproducibility should be high there but we mostly do not read the published research in this connotation and we do not try or test it. Our focus is mostly on replicability. In order to make the research work reproducible, the researchers should write detailed experimental protocol that are easy to understand and implement. Now why this is important that such detailed protocols and proper testing conditions should be written for one research. Because we cannot reproduce any research till the time when we do not have clear-cut black and white. Because if we have the same conditions then we will apply all those due and don'ts and we will reproduce that research. Share the research outputs in an open access repository to make them accessible. This is another important thing that when we talk about reproducibility of a research then it is very important to see if in the same testing edition with the same scientific protocols we have applied that research, so were the results accurate and similar? For accurate and similar results we need to publish our research results on an open repository. You must have seen that very few but very authentic research journals also ask for data sets and after that they keep the results in their repository and take permission from you that if a scientific query comes and you want to see the results or use it in your research then you will give permission to use it. So basically this is a very healthy practice that you can test your research by keeping its conditions in front of you. Perform experiments with variation to increase the roboteness of your findings. This is also very important that you can try different kinds of experiments and then you can make your findings better and better. Refrain from data fabrication or manipulation, this is something very important that we talk about repeatedly that data manipulation or fabrication is not at all allowed. This is a very big unethical offense that all researchers should refrain from. However, it is important to note that reproducible research is not always correct. This is very surprising to say that if we believe that whenever the research is being reproduced it would be having the similar result which the original research has given. But this is not correct because when we change the norms, change the testing conditions then our research results can be different. Which can say that the research we talked about earlier is not correctly reproducibility. For example, there are many instances to follow. False positive in published research, we see that a lot of false positives are also published in research and when you do the replicability then false positive and false positive will not come. Then bad quality of data and data analysis, sometimes the cleaning of the data does not remove its outliers and simple data analysis which will make your data analysis a bad data analysis. Then poor study design, if the study design is not properly made then the sample's inclusion or exclusion criteria is not stringent and it is not properly sampled and the frame is not made then the research design will be a poor research design and if you will reproduce it then if it is that poor then it is obvious that its research results can never be authentic. And then missed confounding variables. If the list is not properly made of research's confounding variables then definitely they are going to mislead the results and omitted data points. When you have omitted the data points then you did not clean it properly. If you are putting your data in the SPSS and you did not see the normal curve of your data and you did not apply any testing conditions on it then the results of your research can be unvalid. And the result is that when you will reproduce that data then those results will also be incorrect.