Приклади вживання Researchers often Англійська мовою та їх переклад на Українською
{-}
-
Colloquial
-
Ecclesiastic
-
Computer
Researchers often associate it with Vikings.
This led to a replicationcrisis instead, with researchers often unable to repeat the results of their studies.
The researchers often call it the phase of slow sleep.
In order to study the Earth and use geodesy today, researchers often refer to the ellipsoid, geoid, and datums.
Researchers often want to summarize the data they have.
This has led to a great deal of misunderstanding, with researchers often arguing about very different things that are designated by a single term.
Researchers often specify a thermal, mechanical or chemical lithosphere in their papers.
Because organizations are so nuanced, CSCW researchers often have difficulty deciding which set(s) of tools will benefit a particular group.
Researchers often struggle to describe their ethical thinking to each other and to the general public.
Despite the important differences between experiments and randomized controlled experiments,social researchers often use these terms interchangeably.
Social researchers often focus on what Kleinberg et al.
To efficiently classify thethousands of images accumulated during a given survey, researchers often upload them to a public, online database where volunteers click through images and identify species.
And because researchers often use a small sample size in a specific setting, it's hard to generalize their results.
In the early days of artificial intelligence research,leading researchers often predicted that they would be able to create thinking machines in just a few decades(see history of artificial intelligence).
Researchers- Often called marine biologists, aquatic biologists or aquatic ecologists, researchers study the creatures found in aquatic environments.
Groups of researchers often experiment with video content using neural networks.
Researchers- often in collaboration with companies and governments- have more power over participants than in the past, and the rules about how that power should be used are not yet clear.
A group of researchers often experiment with video content by using neural networks.
As a result, researchers often tend to fudge the outcome by using artificially purified reagents.
Given this fact, researchers often want to create a huge number of groups for post-stratification.
Therefore, researchers often turn to the companies that provide publication services for conducting the analysis of a research article.
As the power of researchers, often in collaboration with companies and governments, continues to grow, it will become increasingly difficult to avoid complex ethical issues.
Because of these problems, researchers often have to employ a variety of statistical adjustments in order to make inference from their sample to their target population.
In scientific experimental settings, researchers often change the state of one variable(the independent variable) to see what effect it has on a second variable(the dependent variable).
Feynman argued that some researchers often produce studies with all the trappings of real science, but which are nonetheless pseudoscience and unworthy of either respect or support.
Qualitative researchers often experience issues such as getting lost after collecting and coding data, overlooking possibilities for developing their ideas, and producing disjointed and mundane reports.
Even within the CSCW field, researchers often rely on different journals, research, contextual factors and schools of thought, which can result in disagreement and confusion especially when common terms in the field are used in subtly different ways("user","implementation", etc.).
In scientific experimental settings, researchers often manipulate a variable(the independent variable) to see what effect it has on a second variable(the dependent variable).[3] For example, a researcher might, for different experimental groups, manipulate the dosage of a particular drug between groups to see what effect it has on health. In this example, the researcher wants to make a causal inference, namely, that different doses of the drug may be held responsible for observed changes or differences.