Change no more than one. Otherwise, you can't tell which changing variable is having the observed effect.
Ideally, you should change only one variable at once.
Sometimes in the real world this isn't possible for any of a variety of reasons (one example is if you're measuring things where you have no control over the input, where you pretty much have to take whatever data you can get). However, in such cases you've got to make at least one more measurement than the number of variables that are changing and solve a system of simultaneous equations. It's a lot more complicated, and may not be possible unless you're absolutely sure you've got the underlying theory worked out (for example, if the dependence on a given variable might be linear, quadratic, or something else, this probably won't work at all, and at the very least you should get a lot more observations to confirm that things are working the way you think).
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Ideally, you should change only one variable at once.
Sometimes in the real world this isn't possible for any of a variety of reasons (one example is if you're measuring things where you have no control over the input, where you pretty much have to take whatever data you can get). However, in such cases you've got to make at least one more measurement than the number of variables that are changing and solve a system of simultaneous equations. It's a lot more complicated, and may not be possible unless you're absolutely sure you've got the underlying theory worked out (for example, if the dependence on a given variable might be linear, quadratic, or something else, this probably won't work at all, and at the very least you should get a lot more observations to confirm that things are working the way you think).
Change no more than one. Otherwise, you can't tell which changing variable is having the observed effect.
Ideally, an experiment should test only one variable (the independent variable) at a time. If you have two or more variables changing at the same time you have no way of knowing which variable is causing your results.
The purpose of a control variable in an experiment is to allow the experiment to come out with accurate results. It makes it a lot easier to measure the results when different things aren't affecting it.
Controlling for a variable is the act of deliberately varying the experimental conditions in order to take a single variable into account in the prediction of the outcome variable. Controlling tends to reduce the experimental error. A control is something that does not change in the experiment.
The independent variable is the part of the experiment that is being tested or the part that is changed by the person doing the experiment. The dependent variable is the part of the experiment that is affected by the independent variable.
Anything that can be changed in any way is a variable. so,,,,,an infinite number. Day, time, heat, light, humidity, speed, what you ate for dinner the Wednesday before you go shopping. So, quite literally, an infinite number. Hope this helps.