A predictive tool that takes past values of two or more variables to build an equation that is
used to predict future values of one of the variables. - Answers Regression Analysis
An associative tool that measures the strength and direction (positive or negative) of the
relationship between two (or more) variables; but it is not used to make forecasts. - Answers
Correlation Analysis
While in _____ the emphasis is on predicting one variable from the other. - Answers regression
In _____ the interest is directional, one variable is predicted and the other is the predictor. -
Answers regression
While in _____ the emphasis is on the degree to which a linear model may describe the
relationship between two variables. - Answers correlation
In _____ the interest is non-directional, the relationship is the critical aspect. - Answers
correlation
Remember that correlation does not mean - Answers causation.. One can not draw cause and
effect conclusions based on correlation.
There are two reasons why we can not make causal statements - Answers 1. We don't know the
direction of the cause - Does X cause Y or does Y cause X?
2. A third variable "Z" may be involved that is responsible for the covariance between X and Y
Which variable is being predicted or estimated? - Answers Dependent variable (y)
Which variable provides the basis for estimation? - Answers Independent variable (x)
Which variable is the predictor variable? - Answers Independent (x)
Which variable is the variable used to forecast the other variable? - Answers Independent (x) is
used to forecast dependent (y)
What is the y and x between sales and advertising? - Answers Sales [dependent] (y) depends on
advertising [independent] (x)
Which relationship between x and y is direct? - Answers positive relationship (moving in same
direction)
Which relationship between x and y is inverse? - Answers negative relationship (moving in
opposite direction)
Which relationship exists with any increase in the independent variable (x), we except the
dependent variable to increase as well vise versa? - Answers positive relationship