Contents
What if my dependent variable is not normally distributed?
In short, when a dependent variable is not distributed normally, linear regression remains a statistically sound technique in studies of large sample sizes.
What if a variable is endogenous?
An endogenous variable is a variable in a statistical model that’s changed or determined by its relationship with other variables within the model. In other words, an endogenous variable is synonymous with a dependent variable, meaning it correlates with other factors within the system being studied.
Is income an endogenous variable?
In economic or statistical models that include income, it is considered to be an endogenous variable. For example, changes in income are dependent on variables such as changes in consumer expenditure or changes in consumers’ buying power.
Which is the best definition of an endogenous variable?
What Is an Endogenous Variable? An endogenous variable is a variable in a statistical model that’s changed or determined by its relationship with other variables within the model. In other words, an endogenous variable is synonymous with a dependent variable, meaning it correlates with other factors within the system being studied.
How to transform a normal distribution to a non-normal distribution?
Essentially it’s just raising the distribution to a power of lambda (λ) to transform non-normal distribution into normal distribution. The lambda (λ) parameter for Box-Cox has a range of -5 < λ < 5. If the lambda (λ) parameter is determined to be 2, then the distribution will be raised to a power of 2 — Y 2.
Is the outcome dependent variable a continuous variable?
As you mentioned, you outcome dependent variable should be continuous. You do not check the distribution on dependent variable itself. You need check it in the regression process. As many answers mentioned, the residuals are independent and identical normal distributed rather than the outcome itself.
When do residuals not follow the normal distribution?
If the points start curving away from the line at one end for example, then your residuals don’t follow the normal distribution. Simin – You can look at the distribution of residuals to study both nonlinearity and heteroscedasticity. Some econometrics books could be helpful – say by Maddala, for instance.