If you're performing an experiment in which your result depends on multiple variables, but you're just interested in how one of those variables effects the result, you would generally keep all of the other variables constant in order to negate their effects. Those variables that you're keeping constant are called control variables, and you would choose them based on the experiment.
For example, say you wanted to determine how changes in resistance effect a circuit's current. Well, current is dependent on not only resistance, but voltage as well, and since you're only interested in the effects of resistance, you would make voltage the control variable, keeping it constant.
it is for ex; mi project has temperature and insulation as a controled variable or you could also say that it is what you do to get your answer .Wich is really your procedurs miched with your controled variables ps we are talking about science right ;D
I don't really know but usually it is done with one variable. If it has two variables there might be two unknown anwers to the equation.
In a scientific experiment there are different variables. Variables being the factors that you can alter to obtain your results. The independent variable is the factor that you directly alter and the dependent variable is the one that is affected by this. E.g. You pull a cart over 1m and measure the time taken. The force you exert is the independent variable as you are controlling it and time is the dependent variable because it is the variable that is affected by the force you exert. Like if you pulled it really hard the time taken would be really short, and if you pulled it gently the time taken would be really long, etc.
That really depends on the language. Some languages have "constants" separate from "variables"; in Java, for example, the "final" keyword is used to have a variable that can't be changed once it is assigned a value.
they are used for x and y data when x doesnt really relate to y
It doesn't make much difference which letter or letters you use as variables, so it doesn't really mean much.
The purpose of a control group is to show what would happen under normal conditions. It serves as a comparison to the results you receive from the manipulation of the independent variable on the dependent variable. If a control group is present in an experiment, one can be more certain that the independent variable is really responsible for the observations.
Polluting the global namespace with variables that have no reason to be global is never a good idea. Aside from anything else, the programmer has no control over what code may access a global, and global variable declarations may be spread over many files or hidden within headers, making it difficult to get an overview of every global. Globals are not necessarily a bad thing; if a concept is global in nature then of course make it global. But don't make variables global in the mistaken belief that it is somehow convenient. If a variable really needs to be shared amongst a specific set of functions then there are far better ways of doing so without making the variable global to all functions. Declaring the variable locally in a function (even the main function as a static variable) and passing it to the functions that operate upon it, or by encapsulating the variable in a class along with the functions that operate upon it are far better options than making a variable globally accessible. Keeping variables as close to the code that operates upon them makes your code easier to both read and maintain.
In a ploynomial or differential equation or really any formula or equation with variables in it, the coefficients are the terms "in front of" the variable or multiplied the variables. Each variable generally has its own coefficient. If a coefficient is constant (ie just a number) then it is a constant coefficient. eg Consider the polynomial , 3x2+9yx+6 in terms of x. It has one constant coefficient (3), one variable coefficient (9y) and one constant (6).
A controlled experiment means that you try to keep all the variables that are involved in the experiment under control apart from the Dependent and the Independent variables to make sure that any results obtained from the experiment have been affected by the independent variable and not some other extraneous variable. It also ensures that the experiment would have high validity. That is, if the experiment has really measured what it was supposed to measure.
dependent variables, independent variable, nominal, ordinal, interval, ratio variableThere are three main kinds:Nominal: such as colour of eyes, or gender, or species of animal. With nominal variables there is no intrinsic sense in which one category can be said to be "more" than another.Ordinal: Such as Small/Medium/Large, orStrongly Disagree/Disagree/Indifferent/Agree/Srongly Agree. The categories can be ordered but the differences between pairs is not comparable. For example, it is not really possible to say that the difference betwen Strongly disagree and disagree is the same as (or double or half or whatever) the difference between indifferent and agree.Interval: These are variables where the distance between one pair of values (their interval) can be related to the distance between another pair. Such variables can be subdivided into discrete and continuous.Another way of classifying variables is independent and dependent.The dependent variable is a random variable but the independent variable can be random or non-random.
I do it by using an "if/then" statement. The variable behind the "if" statement is the independent variable. The variable behind the "then" statement is the dependent variable. Example: y = 3x3 + 4x2 - 6x +1 So if you tried "if y = 2", you're still stuck on your "then" statement. You don't really know what x is, do you? But if you try "if x = 1", then you can determine right away that y = 2. So x is your independent variable and y is your dependent variable.