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 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
On the outside of the Punnett Square you put the genotype or two alleles of the parents.
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.
i would assume you would just cross seedless oranges but is there a more scientific explanation? i would assume you would just cross seedless oranges but is there a more scientific explanation?
This is actually a little bit of both. Organisms that stayed somewhat the same needed to stay in similar climate situations. However, some organisms mutated or evolved to changing conditions, and were able to withstand various climates.
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
Yes.
I assume you're asking how many famous scientists are Christians.The vast majority of renowned scientists are atheist or agnostic.
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'.
Earth scientists assume that the causes of natural events or phenomena can be determined by observing patterns, collecting data, and analyzing evidence. They use methods such as experimentation, modeling, and field studies to understand the underlying processes driving these events. By studying these factors, scientists aim to develop theories and explanations that can help predict and mitigate future events.
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.
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.