Abdalmuttaleb - Variables are defined as the properties or kinds of characteristics of certain events or objects. Independent variables are variables that are manipulated or are changed by researchers and whose effects are measured and compared. The other name for independent variables is Predictor(s). The independent variables are called as such because independent variables predict or forecast the values of the dependent variable in the model. The other variable(s) are also considered the dependent variable(s). The dependent variables refer to that type of variable that measures the affect of the independent variable(s) on the test units. We can also say that the dependent variables are the types of variables that are completely dependent on the independent variable(s). The other name for the dependent variable is the Predicted variable(s).

I think that you can use the Correlation which is a bivariate analysis that measures the strength of association between two variables and the direction of the relationship. In terms of the strength of relationship, the value of the correlation coefficient varies between +1 and -1.

Abdalmuttaleb AL-sartawi

If you want to find out simple relationship between two quantitative variables the go to Karlpearson correlation analysis. And if you are handilling with qualitative vaibles then use Sperman Rank Correlation analysis. If Your objectives are to predict the one variables on the basis of another varibles the use simple regression analysis. It should be clear that what you want to test and what type data you are handelling. For the validity, go for appropriate testing of hypothesis.

Thank you.

First and foremost it is important to clarify the type of data your study holds. If you know the distribution of your variable, you can either choose a type of regression analysis that responds to the quality of your dataset. Always keep in mind that your dataset determines your choice of method of analysis. This should be cleared before you collect your data. Best of luck.