16. Amelia used a random sample of 100 accounts receivable to estimate the relat

Question

16. Amelia used a random sample of 100 accounts receivable to estimate the relationship between Days (number of days from billing to receipt of payment) and Size (size of balance due in dollars). Her estimated regression equation was Days = 22 + 0.0047 Size with a correlation coefficient of .300. From this information we can conclude that A. autocorrelation is likely to be a problem B. 9 per cent of the variation in Days is explained by Size. C. the relationship between Days and Size is significant. D. larger accounts tend to take less time to pay. 17. If you re - run a regression, omitting a predictor X5, which would be unlikely? A. The new R' will decline if X5 was a relevant predictor. B. The new standard error will increase if X5 was a relevant predictor. C. The numerator degrees of freedom for the F test will increase D. The remaining estimated s will change ifXs was collinear with other predictors 18. If X2 is a binary predictor in Y=A+AX, +AX2 then which statement is most nearly correct? A. X2-1 represents the most desirable condition B. X, would be a significant predictor if ,-423.72. C. X2-0, X2-1, X2-2 would be appropriate if three categories exist. D. X2 will shift the estimated equation either by 0 units or by 2 units 0.213 t then 19. If the fitted annual trend for a stock price is y/t-27 e A. the slow growth rate is not very attractive. B. the stock price seems to be approaching an asymptote. C. the stock is probably undervalued in today's markets D. the stock would more than double every 4 years 20. If a quadratic trend is fitted, and is compared to a linear trend, then the quadratic R' A. will be at least as large as the linear R B. will probably be lower than the linear A C. may be higher or lower than the linear R'. D. cannot be compared to the linear R' (different units)

Explanation / Answer

Q.16 We will check option 1 by one

Option a : There is no provision of autocorrelation here so wrong option.

Option b : Here r = 0.3 so r2  = 0.09

so Yes this option is correct as 9% variation in days is explained by size.

Option c : The relationship is not significant as r2 value is very less.

Option d : Incorrect as relationship is a positive relationship. More size tend to more days.

Option B is the answer

Question 17

Option a : It can happen as x5 is a relevant predictor so it can reduce R2.

OPtion b : Yes, it can also happen as standard error may increase.

Option c: Numerator Degree of freedom will increase. That's impossible. These degree of freedom will reduce by -1 as there is a decrease in number of independent variables.

option d : Yes, the remaining betas will change for sure if there is some collinearity.

Option C is correct here.

Question 18

option a: X = 1 is one of the condition. Not the desired condition. Both conditions are equally desirable.

option b : Significance doesn't individually depend on the value of b2 . It will also depends on the value of standard error of the variable.

option c: Its binary, so three condition can't exist.

option d : Yes if X = 0, no change bu if X = 1 it will increase the predicted value by b2.

Question 19

option a : Growth rate is exponential so not a slow rate of growth.

option b : exponential functions will reach to infinity so no asymptote

opton c : Can't compare . As data is insufficient to compare with other stocks.

option d: y(t+4)/ yt = e ^ (0.213 *4) = 2.345 (yes true statement)

Option D is correct.

Question 20

It will be at least as large as the linear R2 . The statement is obvious as the quadratic trend is fitted so it will have more R2 value.  

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