No, it does not. In fact, for many statistical analyses, it is a definite advantage.
The relationship is a matter of cause and effect. An independent variable is given as one upon which another variable depends. So, for example, if you heat a metal pipe, the pipe expands. The amount of expansion is dependent upon the amount of heating that occurs, so expansion is the dependent variable, and the heating, which you may or may not control, is the independent variable. All it means is that if the independent variable ungoes a change, there is an associated and predictable change in the dependent variable. The two are linked inextricably, but one is cause, the other is effect, or to put it another way, you control the change in the dependent variable with input into the independent variable, but it doesn't normally work the other way around.
Co-efficients normally live in front of the variable.
MathematicsY is often used as the "dependent variable" which changes as the independent variable (X) changes, according to the defined function y = f(x).ExperimentationThe dependent variable is what will change in the experiment, based on changes made to the independentvariable. The constant or controlled variable is maintained so that the outcome is dependent on the changes to the factor being studied.Example : Determining growth of bacteria in various aqueous nutrient solutions.The growth rate (what you measure) is the dependent variable.The amount of a nutrient added is the independent variable.The temperature and humidity are the controlled variables, which are kept the same.Example: Time is an independent variable, no matter how fast you are going, the amount of time does not change over a specific interval. Distance is a dependent variable. The distance travelled is dependent on how fast you are going over that same interval.A dependent variable is a value that receives its magnitude due to the magnitude of the other variables in the "equation" or "test" or "experiment".* * * * *In many situations, though, there is no independent variable but two [inter-]dependent variables. This is particularly true of systems in which there is some sort of feedback. For example, changes in the rate of inflation affects the rate of unemploment and changes in the rate of unemployment affects inflation.A dependent variable is what you measure in the experiment and what is affected during the experiment.
MathematicsY is often used as the "dependent variable" which changes as the independent variable (X) changes, according to the defined function y = f(x).ExperimentationThe dependent variable is what will change in the experiment, based on changes made to the independentvariable. The constant or controlled variable is maintained so that the outcome is dependent on the changes to the factor being studied.Example : Determining growth of bacteria in various aqueous nutrient solutions.The growth rate (what you measure) is the dependent variable.The amount of a nutrient added is the independent variable.The temperature and humidity are the controlled variables, which are kept the same.Example: Time is an independent variable, no matter how fast you are going, the amount of time does not change over a specific interval. Distance is a dependent variable. The distance travelled is dependent on how fast you are going over that same interval.A dependent variable is a value that receives its magnitude due to the magnitude of the other variables in the "equation" or "test" or "experiment".* * * * *In many situations, though, there is no independent variable but two [inter-]dependent variables. This is particularly true of systems in which there is some sort of feedback. For example, changes in the rate of inflation affects the rate of unemploment and changes in the rate of unemployment affects inflation.A dependent variable is what you measure in the experiment and what is affected during the experiment.
MathematicsY is often used as the "dependent variable" which changes as the independent variable (X) changes, according to the defined function y = f(x).ExperimentationThe dependent variable is what will change in the experiment, based on changes made to the independentvariable. The constant or controlled variable is maintained so that the outcome is dependent on the changes to the factor being studied.Example : Determining growth of bacteria in various aqueous nutrient solutions.The growth rate (what you measure) is the dependent variable.The amount of a nutrient added is the independent variable.The temperature and humidity are the controlled variables, which are kept the same.Example: Time is an independent variable, no matter how fast you are going, the amount of time does not change over a specific interval. Distance is a dependent variable. The distance travelled is dependent on how fast you are going over that same interval.A dependent variable is a value that receives its magnitude due to the magnitude of the other variables in the "equation" or "test" or "experiment".* * * * *In many situations, though, there is no independent variable but two [inter-]dependent variables. This is particularly true of systems in which there is some sort of feedback. For example, changes in the rate of inflation affects the rate of unemploment and changes in the rate of unemployment affects inflation.A dependent variable is what you measure in the experiment and what is affected during the experiment.
I am not really sure what you are asking, but a dependent system is a system that has a variable for an answer, therefore the answer can be any real number and the system has a infinite number of answers. Hope that helped
The independent variable, if there is one, is usually plotted on the x-axis, not the y-axis. So the question is based on false premises. The practice of putting the dependent variable on the vertical, y-axis is just a matter of convention. There is no mathematical justification for it.
The factor that changes in an experiment because of the manipulated variable is called the dependent variable. It is the variable that is measured or observed to see how it is affected by the changes in the manipulated variable.
The importance is that the sum of a large number of independent random variables is always approximately normally distributed as long as each random variable has the same distribution and that distribution has a finite mean and variance. The point is that it DOES NOT matter what the particular distribution is. So whatever distribution you start with, you always end up with normal.
It means that the dependent variable and all its derivatives are multiplied by constants only, not by themselves nor by functions containing the independent variable.. For example, (dy/dx) + xy = 0 is non-linear but (dy/dx) + y = (x^2)coswx is linear. (Note that it doesnt matter how the function of the independent variable is)
i thing stars
Gas.