It depends on what you are trying to describe.
These are common words, but in the areas of algebra and statistics, they are terms which need clear definitions.
A variable is represented by a symbol with a value that varies. (see related link)
Attribute data is data which shows the absence or presence of a characteristic. In quality control, a piece is either acceptable or unacceptable. A car is either new or used.
Attribute data can be represented by a binomial variable. Frequently, 0 is off/ no/ absent and 1 is on/yes/ present.
A second definition for "attribute" (not attribute data) when used with a particular object. In this case an attribute can be considered a certain quality or characteristic, like the color of a car.
I have included a related link.
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A normal attribute is an attribute present in a schema and which has to be entered while entering a tuple.A derived Attribute is one which can be inferred(derived) from another normal attribute and it need not be a part of a schema.For e.g.-> In a schema, Date-of-Birth is a normal attribute.While Age is a derived attribute which can be derived from the Date-of-Birth
A line graph is most useful for representing how one variable influences another variable.
A Boolean variable is a variable from Boolean algebra having one of only two values.
linear equation in one variable
Basically the fact that some variable is squared - or that one variable is multiplied with another variable.