To interpret the coefficient of a dummy variable is to follow all of the steps of the equation that is being used as if the dummy variable was a real one.
Chat with our AI personalities
There are various forms. In linear programming, a dummy variable may be used to convert an inequality into an equation. For example x < 10 can be written as x + u = 10 where u > 0. In this case, it is also called a slack variable. Dummy variables are used in regression to indicate the presence or absence of a factor, or for binary variables. For example, male/female could be coded numerically as 0/1 where, because the question is binary, the exact coding does not matter.
A correlation coefficient can only range from -1.0 to 1.0 so a 50 is not possible. Did you mean .5?
There is not enough information to say much. To start with, the correlation may not be significant. Furthermore, a linear relationship may not be an appropriate model. If you assume that a linear model is appropriate and if you assume that there is evidence to indicate that the correlation is significant (by this time you might as well assume anything you want!) then you could say that the dependent variable decreases by 0.13 units for every unit change in the independent variable - within the range of the independent variable.
The further the correlation coefficient is from 0 (ie the closer to ±1) the stronger the correlation.Therefore -0.75 is a stronger correlation than 0.25The strength of the correlation is dependant on the absolute value of the correlation coefficient; the sign of the correlation coefficient gives the "relative" slope of correlation line:+ve (0 to +1) means that as one variable increases the other also increases;-ve (0 to -1) means that as one variable increases the other decreases.
No, it depends upon the size of the coefficient of correlation: the closer to ±1 the stronger the correlation.When the correlation coefficient is positive, one variable increases as the other increases; when negative one increases as the other decreases.