Replication, in this sense meaning getting the same results from the same experiment, is the only way to verify that the observations were not the result of some error, or of some random factor that only affects the experiment in some cases but not all cases. For example, the result of a botany experiment may be completely different if the air temperature and relative humidity varies, as these can affect plants. For bacterial experiments, accidental contamination of containers can skew the results by introducing other organisms (that could either promote or hinder growth).
When an experiment is repeated several times, there is a better chance that the data is correct and the conclusions are valid. Another term used for this concept is reproducibility.
It is important to design an experiment that can be replicated because, some results may have been skewed or wrong. Doing multiple trials helps provide assurance that the results are correct, and it also allows you to get an average in some cases. Observed results are less likely to be affected by random chance.
An experiment that can't be replicated will be viewed as invalid.
Replicated results prove that the observations in the experiment were not just a fluke.
Observed results are less likely to be affected by random chance.
Observed results are less likely to be affected by random chance.
Nitrogen is used for DNA replication, so you need it for cell replication and growth.
It is more important for DNA replication to be exact than for transcription or translation to be exact because replication products the master copy. Translation and transcription contains many possible codes that can correct for errors.
Because RNA is the replication of DNA.
Observed results are less likely to be affected by random chance.
Observed results are less likely to be affected by random chance.
Observed results are less likely to be affected by random chance.
Replication
replication
Replication
Replication should be included in an experimental design because of the way data is analyzed using statistics.
When doing experimental research, it is important to limit
it is important because without same replication you will have a mutation
False
Replication should be included in an experimental design because of the way data is analyzed using statistics.
Replication should be included in an experimental design because of the way data is analyzed using statistics.