An independent variable is a variable which, in the context of the experiment or the observations, can affect the dependent variable but is not affected by it. By contrast, the dependent variable is affected by changes in the independent variable. It is quite possible that there is no independent variable, as such, and each variable affects the other.
Table The difference in the values of the "dependent" variable is a fixed multiple of the difference between the corresponding values of the independent variable. And the value of the dependent variable is non-zero when the independent is zero.Graph A non-vertical straight line which does not pass through the origin.Equation y = mx + c (or equivalent) where m is some real number and c is non-zero.
Yes it depends on what you are measuring in your study. some examples of variable include age, sex, marital status among others
They can do, but there are some circumstances where they may not be particularly useful. If, for example, the observations are not in order of the values of the independent variable, then a line plot will be difficult to read. If there are several different values of the dependent variable for a single value of the independent variable, the graph may be difficult to interpret. If there are two or more observations where the values of both variables are the same, the graph may not indicate that the point is in fact a multiple observation.
The quantity of coffee that is consumed per some measure of time within a period starting some fixed amount of time before the test. Ideally, any study should also take account of the strength of the coffee, and the body mass of the consumer.
Independent event: I fall down from a 100 metre high point without any protective gear. Dependent event: I die.
Yoga can be an independent variable in some experiments and a dependent variable in others.
Independent variables are variables that can be changed in an experiment, while dependent variables are variables that change as a result of an experiment. In other words, independent variables are what you change, and dependent variables are the results of the experiment.
The independent variable determines the value of other variables and is change by the person doing the experiment. The dependent variable is what is affected by the independent variable; it "depends" on the independent variable.
It depends on the context in which x is being considered. In statistics, if x represents the independent variable, then it is considered independent. However, if x represents the dependent variable, then it is considered dependent.
The answer depends on the context. A variable can be independent in some studies but dependent in others. Time can be an independent variable in distance-time or speed-time studies but the time (to failure of a component) is a dependent variable. Perhaps confusingly, the same two variables can swap places depending upon the context. Suppose I believe that healthier people are taller (their growth is less likely to be stunted by illnesses) then my independent variable is some measure of their health and the dependent variable is their height. If instead, I believe that taller people are healthier (their parents must have had good genes) then the independent variable is height and the dependent is health.
I hope this helps you out a lot. If you are asking what a dependent variable is, here is your answer: A dependent variable is a variable which would be the output of the experiment. The value of the dependent variable depends on the value of the independent variable. If you are asking what a dependent variable does, here is your answer: A dependent variable shows you the output of the experiment. It shows you the independent variable's function. If you have learned that in Math, you should understand. Source(s): I'm a Science and Math whiz.
yes. usually you will work with an equal amount of dependent and independent variables. (ie, one dependent variable for every independent variable, and such that there is some kind of relationship between each..) If only. Usually a variable depends on many other variables. Such as, the price of a house depends on its size, number of rooms, distance to schools, age, windows etc.
The factor in an experiment that responds to the manipulated variable
They are the variables that you think predict some outcome (which is considered the dependent variable). So you might have a theory that gender and age predicts personal income. Gender and age are the independent variables, and income is the dependent. The choice of whether a variable is independent or dependent often is driven by the question you're trying to answer. So in many cases it's possible that the same variable could be an independent variable in one analysis, but a dependent variable in a different analysis. For example, while income was the dependent variable in the earlier example, if you were trying to predict whether a child goes to college, the parents' income might be an important independent variable in that case.
It depends on the experiment. In an experiment, the independent variable is the one whose value is changed by the scientist. The change in the dependent variable is studied to see if it correlates to the change in the independent variable.But because age is only dependent on the passage time, which can't be affected very easily, it's probably the independent variable.
The usual way is to plot the independent variable on the horizontal, and the dependent variable on the vertical. There are some where the dependent is on the horizontal, though. Supply-Demand and Price graphs in Economics comes to mind, as an example.
well dependent is when you are are NOT independent so in your daily life you could just have S.E.X and then that is how you become non independent