Yes. Which why life is complicated.
In a controlled experiment, there is typically one independent variable. This is the variable that researchers manipulate to observe its effect on the dependent variable. Keeping all other variables constant allows for a clear understanding of the relationship between the independent and dependent variables. However, some experiments may include multiple independent variables, but each one must be tested in a controlled manner.
One is dependent and one is independent
this is an experiment that only one varible is manipulated at a time
Independent variable is one that does not vary with respect to other variables while other variables called the dependent variables varies with the variation of the independent variable. for ex: if 'x' is is an independent variable that represents say 'time' lets take another variable the dependent like volume(v) . now we say the volume (v) varies with respect to time and not the other way. so, here 'x' is independent variable & 'v' is dependent variable
It can have as many as it needs. You can even change different variables at the same time and study their individual influence with proper statistical tools in many type of experiments.
Simple regression is used when there is one independent variable. With more independent variables, multiple regression is required.
Because if you have none, there is no point in doing the experiment. If you have more than one you will have interactions between the independent variables but, with a good experimental design, these can be estimated so there is no reason to use independent variables one at a time.
1
One is dependent and one is independent
It depends on the number of variables and their nature: 2 variables, both independent: either axis 2 variables, one independent: x-axis 3 variables, all independent: any axis 3 variables, 2 independent: x or y-axis. 3 variables, 1 independent: x-axis. and so on.
Independent variables are those that you change in an experiment. Dependent variables are the ones that you measure in an experiment. Dependent variables are influenced by the independent variables that you change, so they are dependent upon the independent variable. Generally, experiments should have only one independent variable.
this is an experiment that only one varible is manipulated at a time
If one of the variables affects the outcome of the other but not the other way around, then the one that is affected is the dependent and the other is independent.
False. A well-designed experiment can have more than one independent variable if the relationship between them needs to be studied. However, controlling for multiple independent variables can increase the complexity of the experimental design and analysis.
There can only be one independent and one dependent variable. All other variables should be classed as control variables and must be kept constant to achieve a fair test.
I want to develop a regression model for predicting YardsAllowed as a function of Takeaways, and I need to explain the statistical signifance of the model.
One would be the independent variable.