Not exactly sure what you mean by "can't change." However, I if I do understand you correctly, the dependent variable CAN change. The dependent variable will change according to the independent variable's value and overall effect. For example, in an experiment involving water's effect on plants, the dependent variable may be the height of the plant or the glucose produced. Based on the amount of the independent variable (represented on the x axis of a data graph), the dependent variable will increase or decrease. In this case, both dependent values (glucose and height) would probably increase.
Independent and dependent variables are graphed on the axes of a rectangular grid (e.g. graph paper). The important thing is to understand which is which. The independent variable is graphed on the horizontal (x-) axis. In an experiment you choose values of the independent variable and measure the values of the dependent variable (it "depends' on the other). The dependent variable is graphed on the vertical (y-) axis.
they are easier ways to write the answer out and make the answer easier to understand
an independent variable is a thing you can change on your own. a depentent variable is a variable you depend on and a responding variable is a variable that reacts to the experiment
The independent variable. The output variable is dependent on this variable's value and so is called the dependent variable.
the variable that decribes the numbers are reallt tricky to understand but the variable is the dependent variable! (pretty sure but not completely) hope it help you!
A dependent variable is the outcome that is being measured or tested in an experiment or study. It is influenced by the independent variable, which is the variable that is manipulated. The dependent variable is what researchers are trying to understand or predict based on the changes in the independent variable.
A dependent variable is the outcome or result in an experiment that is measured or observed. It is influenced by changes in the independent variable, which is controlled or manipulated in the experiment. The dependent variable is what researchers are trying to understand or explain through their study.
The variable that social scientists refer to as the causal variable is the one that is believed to directly influence or cause changes in another variable. This variable is often the focus of research and analysis to understand its impact on the outcome of interest.
the independent variable is the factor of an experiment that is altered in an attempt to understand its effects on the experiment's subject
Variable names are used so the code is readable. When the code is compiled to machine languages, it no longer uses the variable names to understand it's operations...sometimes variable names are kept as metadata to help debug but the computer does not need them to execute the program...they are for us so we can easily understand what we are doing.
The mediator variable explains the relationship between the independent variable and the dependent variable.
The outcome variable is the dependent variable in a statistical analysis that is being measured or predicted based on changes in other variables, known as independent variables. It is the variable of interest that is being studied to understand its relationship with other variables.
Variable names should show what data the variable holds so others reading your code will understand it. For example, a variable holding the age of a user should be called "age" or "user_age", or something similar.
An outcome variable is the dependent variable in a study that researchers measure to determine the effect of the independent variable(s). It represents the main result or effect that researchers are studying or trying to understand.
An idea about what happens to one variable when a second variable changes is called correlation. Correlation measures the strength and direction of the relationship between two variables. It can help us understand how changes in one variable may be associated with changes in another variable.
Scientists change only one independent variable at a time in an experiment to accurately determine the effect of that specific variable on the dependent variable. By isolating one variable, researchers can understand its impact without any confounding factors, making it easier to draw meaningful and reliable conclusions from the results.