The main possible advantage is that in an experiment, it is possible to control some of the variables so that it is easier to measure the effect of key variables. In observational studies, no such control is possible.
Binomial distribution is the basis for the binomial test of statistical significance. It is frequently used to model the number of successes in a sequence of yes or no experiments.
Qualitative observation takes in mainly the qualities deemed most appropriate for analysis. Quantitave observation takes in the quantities which analytical evidence is mainly suggestive. You may ask "Which is the most important?" That is mainly a subjective issue and, as such should be initiated by the mediator rather than that which can be attributed to an othepaecal study. Again, it is important to judge each case on it's own merits but I would suggest that, in terms of jurisprudence, the observational relationship is inverse of the square of the qualitative in reference to the quantitive. Of course you may have heard the phrase "Quality not Quantity" but in the real world this is seldom the case.
shaking the sample before transferring it into a sterile universal bottle is an important step in many microbiological experiments as it helps to ensure that the sample is well-mixed and that any microorganisms present are evenly distributed throughout the sample.
Without random assignment there is a danger of systematic error - or bias - entering into the results. Statistical theory depends on the errors being random and independent error and that is no longer the case without random assignment. In fact, statistical experiments are often "double-blind": even the observer does not know which individual is in which group. This is to prevent unconscious or subconscious messages to affect the outcome (placebo effects).
It is important to include a label on the axis of anygraph.It is important to include a label on the axis of anygraph.It is important to include a label on the axis of anygraph.It is important to include a label on the axis of anygraph.
An important key to good observational records is use of language. Other people can only interpret the words of the person who was doing the observing.
It's important to repeat experiments so then you know that you did the experiment right.
Scientists publish the details of important experiments so that people can recreate it and see the results for themselves.
Only for experiments
It is important that people are not harmed for the sake of science.
what
It's important so that they can perform experiments and gather data.
becuase in OH we learn by doing and psychology enhance our observational learning
Only when experiments are planed, carried out and analyzed can we know if our hypothesis is true and our methods are reliable. Oncethis is achieved, repeating experiments prove validity.
Only for experiments, not practical uses.
what
To not hurt yourself with experiments.