independent variable
the dependent variable cant change the independent varible, but the independent variable can change the dependent varible. (eg: Bob wants to see if the new baseball pitching machine throws better fastballs then his friend. The baseball pitching machine(independent) could change a fastball(dependent), but a fastball(dependent) cant change the baseball pitching machine(independent).
The main advantage is that it allows you to see how different dependent variables change according to changes in the same "independent" variable. It is relatively simple to use two vertical axes for the dependent variables, but the degree to which the two axes relate to one another is arbitrary. Furthermore, if the ranges of the dependent variables are very different the chart becomes unreadable.
This is an abbreviation for independent and identically distributed. In the mathematical analysis of samples, it is convenient to state that each data value in the sample is a iid random variable. See related link.
You may get more ideas from wikipedia under regression analysis. You can do a regression analysis with as little as 2 x,y points- but is it meaningful? Requirements for valid or meaningful relationships can be subjective. However, in my opinion, if meaningful relationships are to be created using regression analysis, the following are important: a) The independent variable should have values that are independent (no relation exists between them). b) There should be a good rational or experimental basis for identifying the independent variables and the resultant dependent variable. c) Sufficient data should be collected in a controlled environment to identify the relationship. d) The validity of the relationship should easy to identify both visually and by numbers (see "goodness of fit" tests).
Generally, when the dependent variable appears to be the result of more than one independent variables, a multiple regression model may be suitable. It is difficult to justify adding an additional variable, that does not significantly reduce the residual error of the fit. The setting of thresholds to justify addition of variables is in the area of "stepwise regression." The data must be adequate and consistent with the assumption of independent variables. I note from the first related link: Most authors recommend that one should have at least 10 to 20 times as many observations (cases, respondents) as one has variables, otherwise the estimates of the regression line are probably very unstable and unlikely to replicate if one were to do the study over. See related links. Many more are available in the Internet. Also, many books have been written on the multiple regression- proper and improper use.
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/Manipulative variable is the variable that you purposely change, and the Dependent/Responsive variable is the variable that changes as a rest of the Independent variable. You measure the dependent variable to see the effects of the Independent variable.
The independent variable. If it changes the other variable, then the other variable depends on it and consequently is the "dependent variable".
The dependent variable is the object(s) being tested in the experiment. So if you were to pop a balloon, then the BALLOON would be the dependent variable. Why? Because it is the object being tested. Hope this helped. -6th grader.
the dependent variable cant change the independent varible, but the independent variable can change the dependent varible. (eg: Bob wants to see if the new baseball pitching machine throws better fastballs then his friend. The baseball pitching machine(independent) could change a fastball(dependent), but a fastball(dependent) cant change the baseball pitching machine(independent).
In experimental design there are two variables, the independent variable and the dependent variable. You are allowed manipulate or change one variable to see how that affects results in an experiment you are conducting. Think of it as the variable Ican change. This is the i variable, the independent. The experiment will generate data that responds to these changes. This data is your dependent variable.
The dependant variable is what you can't change, or decide, and it is affected by the independent variable. EX. If you were to see which liquid is the slowest, the independent variable would be the liquids that you can choose, and the independent variable would be how fast or slow they move, because it depends on what liquids you chose.
An independent variable. This is because you can manipulate the variable so it is said to be independent of the other variables. This is different from the dependent variable which is the variable you are measuring the change in. For example in an experiment to see how the amount of water given to a plant affects it's height, the amount of water is the independent variable, because it is the variable you can change, while the height of the plant is the dependent variable because we want to see how the change in the amount of water affects it.
The dependent variable is the one you are interested in. It's the one you are looking at, to see if it changes. For example: If I want to see if water evaporates faster when it is hotter, I am changing the independent variable, temperature, and hoping to see a difference in the dependent variable, the rate of water evaporation. I would be keeping the controlled variable of water volume the same between each repeat of the experiment, because that could inadvertently change the dependent variable, which I don't want.
the investigator only changes one variable in an experiment because they need to see how that one variable reacts. if you wanted to see how the dependent variable changed but changed the independent variable you would not see how the one variable reacts.
See link for the Wikipedia article. The dependent variable is sometimes called response variable, or outcome variable. During what year of school, K thru 12, do kids experience the greatest average change in height (or weight)? You are "manipulating" what year of school a child is in. You aren't making any changes on this-- this is just your independent variable. You are going to measure height change for each child, so a starting and ending measure is needed. Height is the dependent variable.
An independent variable is something that you can change in your experiment. A dependent variable is something that changes depending on what your independent variable is. Example: You have two plants. You water one every day and you water the other one every other day to see how fast they'll grow. Your independent variable is water, because you can change how much you give to the plant. Your dependent variable are the plants, because they'll change depending on how much water you give them.