I am curious if 5 replicates can get an accurate result of the experiment. Having 5 replication can be accepted? In your own idea or experiences, what are the minimum number of replication must be use in the study?
My study was all about the cassava must be grown in Greenhouse.
Yes if variability is very small and the treatment effect is large. If I have two treatments like this:
1) 10.005, 10.004, 10.007, 10.002, 10.003
2) 37.001, 37.002, 37.001, 37.009, 37.004
I would stop at five replicates. Unfortunately, a greenhouse trial isn't going to be like this.
Much of agricultural research is done with a small number of replicates. While this is accepted, I don't think it is a good idea. Tests have low power (ability to detect a significant difference when a significant difference is present), and often are impossible to replicate. If another scientist redoes your experiment they will likely get a different outcome.
Because there are often space limitations in agricultural research there may be few options. If so, consider running the test with 5 replicates, then redoing the test next month to get another 5 replicates. If at all possible do this one more time just to be sure.
When the replicates are lesser it is better to use a control group to compare....
Dear Jayson
It seems that you have several treatments. If this is the case, then five replications is ok. In solving ANOVA, the error degree of freedom, should be more than 12 to get valid conclusion.
Regards
Rajiv
The number of repeaters in the green house is less than the number of repeaters in the open field, as well as the adoption of a number of repeaters on the soil type
1. Please see this link for "Replicates and repeats in designed experiments", and see what is difference between replicates and repeats. It is from the Minitab site.
[ http://support.minitab.com/en-us/minitab/17/topic-library/modeling-statistics/doe/basics/replicates-and-repeats-in-designed-experiments/ ]
2. Attached 2 papers with case-study about 'replicates'.
It all depends on the quality of the experiments, the magnitude of differences between the treatments, relative to the error, and on the use of common sense. If the results are not conclusive, five replicates are not enough and you should repeat the experiment or modify it´s design. Since repeating experiments in time provides considerably more reliable results than single experiments with many replications, it is better to have several repeated experiments with fewer replications. Bear in mind, that conclusions from your greenhouse experiments are valid only for the greenhouse environment, in which the experiment was done, regardless of their statistical significance. Results from experiments at another date, other greenhouse or outside it might be quite different.
Erik
It depends on type of the experiment. For greenhouse experiments, 4-6 replications are OK. For field experiments 3-4 would be enough. Sometimes, setting up too many replications may increase the experimental error. Anyway, 5 replications for your greenhouse trial are good. Good luck.
Number of repetitions depends on the number of treatments and also differences among treatments. In this regard, there are formulas that determine the appropriate number of repetitions(for example : r>= 2(Zα/2 +Z β/2)2 /(σ/d)2 , steel & torrie) . In any case, it can be concluded that the degree of freedom error usually must be over 10. (dfe>=10).
In general, we should have d.f. error of 12 for testing of treatment significance.
It depends on the number of treatments. However, 3-4 replications are okay for a field experiment.
The probability of achieving a reasonable result depends on the true standard error (s) per unit, the number of replication (r), and experimental error (residual) degree of freedom (dfE) (Cochran and Cox 1957).
It, thus, depends on the number of treatments, availability of material, experimental unit and expenses. In the case of limited resources as minimum as 2 replications can be used provided that the number of treatments is high (say > 20) and in turn the number of dfE is high (say > 19).
Replication main function is bring accuracy and minimize error in data so if resources are available you can opt for 5 but best is maximum 4 to manage collected data accurately. As reported by Cochran and Cox 1957, the probability of achieving a reasonable result depends on the true standard error (s) per unit, the number of replication (r), and experimental error (residual) degree of freedom (dfE).
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