I'm not going to come up with an example for you because I'm not interested in doing your homework. However, I will help you with reasons why we should do these things.
Framing the hypothesis is important to ensure that we have a manageable question to deal with. Its very broad to suggest that candy increases happiness, it would also be very difficult to test every type of candy across a large enough sample and examine every measure of happiness. Its quite another to ask about the effects of chocolate on subjective wellbeing. With that being said, the question remains somewhat vague. Operational definitions help to clear up they hypothesis by limiting the options even more. For example, we could say our IV (chocolate) is actually X brand of Dark Chocolate. This sort of operational definition also helps us in that we are sure of what we're testing, and we can pass that along clearly to future researchers. Further, future researchers aren't unclear of what type of chocolate we're testing, or what measure of subjective wellbeing we are using.
The independent variable determines the value of other variables and is change by the person doing the experiment. The dependent variable is what is affected by the independent variable; it "depends" on the independent variable.
A dependent (responding) variable is a condition that can change as the result of an independent variable's alteration. It can also be referred to as an effect. Every well-designed experiment has three kinds of variables. 1) Control variables, which are the same for each stage of the experiment. 2) Independent (manipulated) variables, which represent what is being changed by experimenters. 3) Dependent (responding) variables, which respond to the change and ideally are the direct result of the change in the independent (manipulated) variables.
Multicollinearity is when several independent variables are linked in some way. It can happen when attempting to study how individual independent variables contribute to the understanding of a dependent variable
MathematicsY is often used as the "dependent variable" which changes as the independent variable (X) changes, according to the defined function y = f(x).ExperimentationThe dependent variable is what will change in the experiment, based on changes made to the independentvariable. The constant or controlled variable is maintained so that the outcome is dependent on the changes to the factor being studied.Example : Determining growth of bacteria in various aqueous nutrient solutions.The growth rate (what you measure) is the dependent variable.The amount of a nutrient added is the independent variable.The temperature and humidity are the controlled variables, which are kept the same.Example: Time is an independent variable, no matter how fast you are going, the amount of time does not change over a specific interval. Distance is a dependent variable. The distance travelled is dependent on how fast you are going over that same interval.A dependent variable is a value that receives its magnitude due to the magnitude of the other variables in the "equation" or "test" or "experiment".* * * * *In many situations, though, there is no independent variable but two [inter-]dependent variables. This is particularly true of systems in which there is some sort of feedback. For example, changes in the rate of inflation affects the rate of unemploment and changes in the rate of unemployment affects inflation.A dependent variable is what you measure in the experiment and what is affected during the experiment.
another name for variables is factors
A prediction that states both an independent and a dependent variable is called a hypothesis. A hypothesis is stated as such: if "independent statement", then "dependent statement."
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.
Independent and dependent are types of variables. These variables are used mostly in science and math. When using independent variables you can control them dependent variables you cannot.
In a hypothesis, the independent variable is the factor that is manipulated or changed, while the dependent variable is the factor that is measured or observed to see how it is affected by the independent variable. The relationship between them is that changes in the independent variable are believed to cause changes in the dependent variable, allowing researchers to test their hypothesis and draw conclusions.
the independent variable controls the dependent variables
Every time the independent variables change, the dependent variables change.Dependent variables cannot change if the independent variables didn't change.
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.
Dependent variable change and independent variables do not change.
One is dependent and one is independent
Independent changes; the dependent variable is what you will measure.
Independent variables are the input value of a function (usually x) and dependent variables are the output value of the function (usually y).
The test variable (independent variable) controls the outcome variable (dependent variable).