The independent variable is the factor in an investigation that the scientist is changing.
The dependent variable is the factor which is measured.
All other variables, factors which could affect the experiment, are controlled, or kept the same.
For example, in an experiment to find out how light intensity affects bean plant growth, the independent variable would be the intensity of the light. The dependent variable would be the amount the plants grew. The controlled variables would be things like the temperature, the acidity of the soil, the amount of water given, the amount of CO2 in the air; in short, anything that could affect the results.
Chat with our AI personalities
It does not have to. It is simply a study where two variables have a joint probability density function. There is no requirement for both variables to be dependent - one may be dependent on the other (which is independent).
The answer to the question depends on what it is that you are trying to study.
Yes. The presumed cause is the independent variable and the presumed effect is the dependent varibale. Variablility in the dependent variable is presumed to depend on variablility in the independent variables. It is used more of a direction of influence rather than a cause and effect scenario. Ex. need for increased assistance is dependent on decrease in health. Health is the independent variable and assistance is the dependent.
Yes, think about cause and effect when thinking about this issue. Even to describe or observe a phenomena.
Either- and most people are ignorant of this fact. If your study is about how the size of the bottle affects the price, then the independent variable is the size of the bottle and the dependent is the price. However, if your study is to determine how the price that you pay affects the size of the bottle, the independent variable is the amount of money and the dependent is the bottle size.