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In a statistical model you have two kinds of variable. Response variables are the "outputs" of your model. Explanatory variables, on the other hand, are the "inputs" of your model. Response variables are dependent on the explanatory variables. Explanatory variable are independent of the response variables.
Imagine you were trying to formulate a statistical model of your car's fuel economy. The "output" of your model is miles per gallon (or kilometres per litre). That's a dependent variable. "Inputs" into your model might be (for example) engine capacity, number of cylinders, tyre pressure, etc. These are your independent variables. That is, fuel economy may be, or is, (to be determined by the modelling) dependent on engine capacity and/or number of cylinders and/or tyre pressure, etc.
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Is there a relationship between the independent variable and the dependent variable?
inferential statistics
What is a factor in statistics?
A factor in statistics can be defined as a variable which will affect the results of an experiment. This is mainly an aspect which is independent.
What serves as a standard of comparison to evaluate the effectof the independent variableon the dependent variable?
In statistics, the standard of comparison is the r2 which is a percentage that explains what percentage of the dependent variable can be accounted for by the independent variable.
What is the manipulating variable the dependent variable or the independent variable?
The independent variable.
What happens when you introduce more than one independent variable into a linear regression analysis?
this is for a class in Math-233-statistics
