Quantitative Methods II (IC) Sem 2 Quiz 1 Ucc CoDE 2020/2021

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1. A decrease in the amount of rain will be accompanied by a decrease in the sales of umbrellas. This is the case of....

2. Which of the following is an example of a curvilinear regression model?

3. If Y = 10 + 35X, the estimated value of Y when X = 20 is....

4. If the coefficient of correlation is -0.85 what will be the coefficient of determination?

5. Which of the following components of a time series deals with patterns of change within a year?

6. If the coefficient of correlation between X and Y is ......0.9648 it means that there is

7. If there is a perfect negative correlation between two variables X and Y Pearson's r will be

The following is a linear regression model. Use it to answer questions 8 - 10.
Y= a + bx


8. In order to test hypothesis about b, one would use the

9. What is 'a' in the regression model?

10. What is 'b' in the regression model?

11. If the relationship between M and N is curvilinear, then as N changes

Suppose the consumer price index for the month of August 2017 was 400 (2014 = 100). Use this information to answer questions 12 and 13.

12. What was the purchasing power of the cedi in August 2017?

13. What was the real income of GHc 255,000?

The prices and quantities purchased of some five items, M, N, O, P and O in 2016 and 2017 were as follows: Use it to answer questions 14 and 15.



Item

2026

2017

Price
(¢000)

Quantity
(000 units)

Price
(¢000)

Quantity
(000 units)

M

3

60

4

80

N

6

30

5

40

O

5

40

8

20

P

2

100

2

150

Q

7

20

10

10

Using 2016 as the base year

14. The simple aggregate price index will be.....

15. The simple aggregate quantity index will be

16. One of the assumptions underlying linear regression is that y values are statistically independent of each other.

17. A decrease in hours of leisure leading to an increase in total productivity. This is a case of positive correlation.

18. The standard error of the estimate is a measure of the degree of dispersion of the y-values around the regression line.

19. Laspeyres quantity index uses the base year quantities as weights.

20. The residual fluctuations are unpredictable but they can be identified.

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