Your answer: C was incorrect. The correct answer was B) There is at least some correlation between the error terms from one observation to the next. When correlation exists, autocorrelation is present. As a result, residual terms are not normally distributed. This is inconsistent with linear regression. Your answer: C was incorrect. The correct answer was B) residuals are mean reverting; that is, they tend towards zero over time. The assumptions regarding the residuals are that the residuals have a constant variance, have a mean of zero, and are independently distributed. Your answer: A was correct! The independent variable is uncorrelated with the residuals (or disturbance term). The other statements are true. The disturbance term is homoskedastic because it has a constant variance. It is independently distributed because the residual for one observation is not correlated with that of another observation. Note: The opposite of homoskedastic is heteroskedastic. For the examination, memorize the assumptions underlying linear regression! Your answer: C was correct! There is no requirement that the variance of the error term should be equal to one. Your answer: B was incorrect. The correct answer was C) An assumption of linear regression is that the residuals are independently distributed. Even when there is a strong relationship between two variables, we cannot conclude that a causal relationship exists. The coefficient of determination is defined as the percentage of total variation in the dependent variable explained by the independent variable.
Linear regression is based on a number of assumptions. Which of the following is least likely an assumption of linear regression? A) Values of the independent variable are not correlated with the error term. B) There is at least some correlation between the error terms from one observation to the next. C) The variance of the error terms each period remains the same. Ans B Which of the following is least likely an assumption of linear regression? The: A) expected value of the residuals is zero. B) residuals are mean reverting; that is, they tend towards zero over time. C) residuals are independently distributed. Ans C The assumptions underlying linear regression include all of the following EXCEPT the: A) independent variable is linearly related to the residuals (or disturbance term). B) disturbance term is normally distributed with an expected value of 0. C) disturbance term is homoskedastic and is independently distributed. Ans A Which of the following is least likely an assumption of a simple regression? A) The expected value of the error term is zero. B) The error term is normally distributed. C) The variance of the error term is one. Ans C Which of the following statements about linear regression analysis is most accurate? A) The coefficient of determination is defined as the strength of the linear relationship between two variables. B) When there is a strong relationship between two variables we can conclude that a change in one will cause a change in the other. C) An assumption of linear regression is that the residuals are independently distributed. Ans C
simi Wrote: ------------------------------------------------------- > Isnt the last one C? > > Yes
ditchdigger2CFA Wrote: ------------------------------------------------------- > Linear regression is based on a number of > assumptions. Which of the following is least > likely an assumption of linear regression? > > A) Values of the independent variable are not > correlated with the error term. > > B) There is at least some correlation between the > error terms from one observation to the next. > > C) The variance of the error terms each period > remains the same. B > Which of the following is least likely an > assumption of linear regression? The: > > A) expected value of the residuals is zero. > > > B) residuals are mean reverting; that is, they > tend towards zero over time. > > > C) residuals are independently distributed. B > The assumptions underlying linear regression > include all of the following EXCEPT the: > > A) independent variable is linearly related to > the residuals (or disturbance term). > > B) disturbance term is normally distributed with > an expected value of 0. > > C) disturbance term is homoskedastic and is > independently distributed. A > Which of the following is least likely an > assumption of a simple regression? > > A) The expected value of the error term is zero. > > > B) The error term is normally distributed. > > C) The variance of the error term is one. > C > Which of the following statements about linear > regression analysis is most accurate? > > A) The coefficient of determination is defined as > the strength of the linear relationship between > two variables. > > B) When there is a strong relationship between > two variables we can conclude that a change in one > will cause a change in the other. > > C) An assumption of linear regression is that the > residuals are independently distributed. > C > (CP gets all the answers right ;-)) He does 
13.B 14.B 15.A 16.C 17.B 18.B 19.A 20.C 21.C
so I am like 2-3 off?
ahhh i missed the crunch. oh well, actually just did a 60 Q test on Quant so i’ve seen most of these.
What? The Lunch Crunch got over already? … It’s lunch time here in India ;-0
Isn’t this B?. ________________ Posted by: cpk123 (IP Logged) [hide posts from this user] Which of the following is least likely an assumption of linear regression? The: A) expected value of the residuals is zero. B) residuals are mean reverting; that is, they tend towards zero over time. C) residuals are independently distributed. Ans C ________________
yep got that one wrong…