Scientists assume that experimental results can be reproduced because they follow very specific steps when conducting experiments. These guidelines are known as the scientific method, and is designed so that experiments can be easily repeated and retested.
The point of experiments is to control the variables. You have to understand it is not that scientists "assume" the results can be produced but rather that is the test of the experiment. If the results can be produced then that means the experiment is sound and solid and conclusions can be safely drawn from the data. If the results cannot be reproduced it means there is a flaw somewhere in the experiment for instance a variable was not taken into consideration or something went wrong.
Good experiments must be repeatable or they arent good they are bad.
The way the universe works now is the same as how it did in the past, as well as how it will work in the future, which is unverifiable and therefore must be assumed. Some examples: - Scientists assume that there is no way to secure complete and absolute truth - Secular scientists assume that the earth and universe were not created supernaturally. - Scientists assume that natural laws we identify will apply to all of the universe - Scientists assume that they all work towards the common good - Scientists assume life can evolve on earth in the presence of water - Most scientists assume near-death experiences and out-of- body experiences are a result of a lack of oxygen in the brain
You are supposed to assume/expect that nothing happens, or the norm happens. E.g. if you are testing if plants grow more in light, you assume they dont, then see if that expectation is consistent with the result.
Biologists assume that the systems they are studying are "representative" of the population as a whole, that is, that the population's test results will be distributed according to the standard curve...ie, that graph of scores that best covers the range of 90% of scores in the entire population. In short, the standard curve provides the baseline by which to compare test results.
On the outside of the Punnett Square you put the genotype or two alleles of the parents.
if a normal cell divides you can assume that
Scientists assume that experimental results can be reproduced because they follow very specific steps when conducting experiments. These guidelines are known as the scientific method, and is designed so that experiments can be easily repeated and retested.
Because we are unaccustomed to the physical laws of the universe changing from moment to moment.
i would assume it is known as a solution
Because we are unaccustomed to the physical laws of the universe changing from moment to moment.
The way the universe works now is the same as how it did in the past, as well as how it will work in the future, which is unverifiable and therefore must be assumed. Some examples: - Scientists assume that there is no way to secure complete and absolute truth - Secular scientists assume that the earth and universe were not created supernaturally. - Scientists assume that natural laws we identify will apply to all of the universe - Scientists assume that they all work towards the common good - Scientists assume life can evolve on earth in the presence of water - Most scientists assume near-death experiences and out-of- body experiences are a result of a lack of oxygen in the brain
answer it
Yes.
I assume you're asking how many famous scientists are Christians.The vast majority of renowned scientists are atheist or agnostic.
Scientists assume that a thin ring in tree growth indicates a period of unfavorable conditions for growth, such as drought, disease, or cold temperatures. These periods can be used to reconstruct past environmental conditions and study the impact of climate change on ecosystems.
I'm not sure but i do believe that there is life out there somewhere
The earth is roughly 4.5 billion years old, give or take a few 'earthdays'.
Statistics are simply a tool to help the experimentalist interpret data in an unbiased manner. When properly employed, statistics will not only tell the scientist how "good" his or her numbers are, but can also lead to improvements in experimental design. However, the most important function of a statistical description of data is to remind the experimentalist not to assume any more about his or her results than the data warrant.