5. Under the Classical Linear Regression model assumptions,
which one of the following is not a required assumption about the
error term ui? *
a. There is no multicollinearity in the model
b. The variance of the error term is the same for all values
of x.
c. The values of the error term are independent.
d. The error term is normally distributed.
6 If you find a positive value of the correlation coefficient
it implies that the slope of...
What is the main assumptions about the behaviour of the
disturbance term in the Classical Linear Regression Model (CLRM).
Briefly explain the meaning of each assumption.
Define and discuss the difference between linear regression and
multiple regression. Are there any assumptions which must be met
before using multiple regression?
When we estimate a linear multiple regression model (including a
linear simple regression model), it appears that the calculation of
the coefficient of determination, R2, for this model can be
accomplished by using the squared sample correlation coefficient
between the original values and the predicted values of the
dependent variable of this model.
Is this statement true? If yes, why? If not, why not? Please use
either matrix algebra or algebra to support your reasoning.