Independent variables:

Independent variables are variables that are manipulated or controlled in an experiment to determine their effect on the dependent variables. These variables are not influenced by any other variables in the experiment.

Dependent variables:

Dependent variables are variables that are observed or measured in an experiment and are expected to change as a result of the independent variable's manipulation. The values of these variables depend on the values of the independent variables.

Relationship between variables:

In some cases, the values of two variables may be independent of each other. This means that changes in one variable do not affect the values of the other variable in any particular direction. In such situations, the two variables are considered to be unrelated or uncorrelated.

Zero correlation:

When the movement in one variable does not produce any movement in the other variable, it indicates a zero correlation between the two variables. Zero correlation means that there is no linear relationship between the variables. It implies that changes in one variable cannot be used to predict or explain changes in the other variable.

Example:

Let's consider an example to understand this concept better. Imagine a study that examines the relationship between the number of hours spent studying and the number of hours spent watching TV per day among a group of students. If there is no relationship between these two variables, we would expect that changes in the number of hours spent studying would not result in any changes in the number of hours spent watching TV.

If the data collected from the study shows that an increase or decrease in studying hours does not lead to any consistent change in TV watching hours, we can conclude that these two variables are unrelated or have a zero correlation.

Conclusion:

In summary, if the movement in one variable does not produce any movement in the other variable in a particular direction, it indicates a zero correlation between the two variables. This means that the variables are independent of each other and changes in one variable cannot be used to predict or explain changes in the other variable.

Uncorrelated