Well according to Aborginal Dreamtime stories, the seagull was originally a giant flying dragon. This flying dragon was the king of the sky, anything that got in its way, was destroyed. But one day a crab accused the dragon of being stingy and not sharing the sky with other animals, this made the seagull very angry, an epic Pokemon battle broke out.
The dragon played with Wingull (a seagull type Pokemon) and the crab used Paras (a crab like Pokemon). They both had direct hits and one hit knockouts!! This left the dragon and crab in confusion for forty years. Eventually the dragon responded and accepted to share the sky with the other animals. So overtime the dragon devolved into a lesser creature from the flying dragon. Now a days we call it the 'seagull' it looks similar to the Pokemon, Wingull, played by there ancestor's.
How ironic.
scientist have been able to infer the relationships between the major groups of vertebrates by bones
I think this type of inference is by looking at the data, i.e., there is no real relationship between the tables (through Primary and Foreign keys), but when you analyze the data in a table you are able to infer that there is a relationship.
You're supposed to infer that there was something more than a friendship between dumbledore and grindelwald, but dumbledore has to destroy grindelwald because he is evil.
ako nga ang naghahanap ng sagot
the sun warms the Earth
The writer is doing a report on the jogger. or The writer is a observing a typical jogger
reaction rate doubles with every 10 K temperature change
critical thinking and infers are bith answers.
One thing you can infer is that they are able to be self-sufficient and survive in the woods, also that their relationship is strong enough that they are able to want to live alone.
DNA analysis is commonly used to determine the similarity between two species. From this, we can infer the evolutionary relationship of those species.
A correlational experiment examines the relationship between variables without manipulating them, while a quasi experiment involves manipulating an independent variable but lacks random assignment of participants to conditions. So, a correlational experiment focuses on the association between variables, while a quasi experiment allows for some degree of causal inference due to the manipulation of an independent variable.
Advantages over what? For what? Generally linear interpolation is done because one infers that the relationship between points is linear and/or it is the the easiest kind of interpolation. In the absence of data or theory to help you infer the relationship between points the principle of parsimony suggest that use the simplest that gets the job done - linear.