Independent variable
The variable used to explain the dependent variable in a regression, also called the explanatory variable. The slope gives the change in the fitted value per unit of it.
Where you will meet it
Independent variable appears in 11 learning outcomes on the CFA syllabus. A few of them:
- Set out what a simple linear regression assumes
“Simple linear regression fits a straight line relating one independent variable to one dependent variable, and it rests on four assumptions: the relationship is linear, the errors have zero conditional mean given the independent variable (they are uncorrelated with it), the errors have constant variance across observations, and the errors are normally distributed.”
- Set out which investment questions multiple linear regression can answer and the steps involved in running one
“Frame the question, choose the dependent and independent variables, then ask whether the dependent variable is continuous; if it is a yes-or-no outcome, logistic regression fits better than ordinary least squares.”
- Explain what the intercept, slope and coefficient of determination mean
“The intercept is the fitted value when the independent variable is zero, which is often outside the range of the data and therefore not meaningful on its own.”
- Apply a regression model to produce a forecast
“A prediction substitutes a value of the independent variable into the fitted equation: predicted y equals the intercept plus the slope times x.”
See also
Practise it
Practise independent variable until it is automatic: questions that explain every wrong option.
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