CLASS: B.A. ECONOMICS 14A / 192
St. JOSEPH’S COLLEGE (AUTONOMOUS) TIRUCHIRAPPALLI – 620 002
SEMESTER EXAMINATIONS – APRIL 2014
TIME: 3 Hrs. MAXIMUM MARKS: 100
SEM SET PAPER CODE TITLE OF THE PAPER
IV 2012 11UEC430404
ALLIED OPTIONAL: STATISTICS FOR
ECONOMICS-II
1. When the variables move in the same direction it is called a) Simple correlation b) Multiple correlation c) Positive correlation d) Negative correlation
2. Regression is a) Independent of origin and scale b) Independent of origin and not of scale c) Independent of origin d) Independent of scale
3. The formula of probability is a) P(A or B) – P(A) + P(B) b) Number of favourable cases/ total no of equally likely cases c) P(A and B) = P(A)

P(B) d) None of the above
4. A mathematical method of fitting ‘best fit line’ to a given data is a) Least square method c) Graphic method b) Semi average method d) Moving average method
5. In India, consumer price Index for working classes is compiled and published by a) The Central Statistical Organization. b) The Labour Bureau in the Indian Economic Journal c) Economic Adviser’s Office d) The Labour Bureau in the Indian Labour Journal

Fill in the blanks:
6. If the relationship is only between two variables, it is called _______.
7. ______ is the square root of the product of the two regression coefficients.
8.
The empirical probability of an event ‘A’ may be expressed as
P(A) = ______.
9. Secular trend refers to the ______ movement.
10. ______ is the suitable average to calculate index number.
State True or False:
11. Correlation tells the cause and effect relationship between two variables.
12. Regression means going back.
13. If a coin is tossed, there are two equally likely results, a head or a tail.
Hence the probability of a head is 1/2.
14. Sales of ice-cream, khadi, cotton clothes and umbrellas are examples for seasonal variation.
15. Index numbers may be used to measure the purchasing power of money.
Match the following:
16. Karl pearson - a)
P
01

 p
1 q
0
 p
0 q
0


 p
1 q
1
 p
0 q
1

100
17. Sir Francis Cotton - b) least squares method
18. Addition theorem - c) P(A or B) = P(A) + P(B)
19. Line of best fit - d) Correlation
20. Fisher - e) Regression

SECTION – B
Answer all the questions: 5 x 4= 20
21. a. The ranking of 10 students in 2 subjects A & B are as follows:
A 6 5 3 10 2 4 9 7 8 1
B 3 8 4 9 1 6 10 7 5 2
Calculate rank correlation coefficient.
OR b. What are the types of correlation?
22. a. The following calculations have been made for prices of
12 stocks (x) on the Calcutta stock exchange on a certain day along with the volume of sales in thousands of shares (y). From these calculations find the regression equation of prices on stocks, on the volume of sales of shares.
 x = 580,
 y = 370,
 xy = 11494,
 x 2 = 41658
 y 2 = 17206
OR b. What are the differences between correlation and regression?
23. a. From a bag containing 10 black balls and 20 white balls, a ball is drawn at random. What is the probability that it is black?
OR b. What is the probability of picking a card that was red or black?
24. a. What are the components of time series?
OR b. What are the merits and demerits of graphic methods of measuring trend?
25. a. What are the uses of index numbers?
OR b. Compute Laspeyre’s index number:
Item
A
B
C
D
Price
Base year Current year Base year Current year
6
2
4
10
10
2
6
12
50
160
60
30
Quantity
50
120
60
25

SECTION – C
Answer any FOUR questions: 4 x 15 = 60
26. The following table gives indices of industrial production of registered unemployed (in hundred thousand). Calculate the value of the correlation coefficient.
Year 1991 1992 1993 1994 1995 1996 1997 1998
Index of production:
Number of unemployed:
100
15
102
12
104
13
107
11
105
12
112
12
103
19
99
26
27. The following table gives the aptitude test scores and productivity indices of 10 workers selected at random.
Aptitude scores:(x) 60 62 65 70 72 48 53 73 65 82
Aptitude scores:(y) 68 60 62 80 85 40 52 62 60 81
Fit regression equations.
28. A problem in statistics is given to 5 students A, B, C, D and E. Their chances of solving it are 1/2, 1/3, 1/4, 1/5 and 1/6. What is the probability that the problem will be solved?
29. Below are given the figures of production (in 1000 quintals) of a sugar factory.
Year 1992 1993 1994 1995 1996 1997 1998
Production
80 90 92 83 94 99 92
(in 000 quintals)
(i) Fit a straight line trend to these figures.
(ii) Estimate the production in 2001.
30.
Using the following data construct Fisher’s ideal index and show that it satisfies Time Reversal and Factor Reversal tests.
Commodity Price (in Rs.)/Unit No. of units
A
B
C
D
E
Base year Current year Base year Current year
6 8 10 12
10 10 5 8
5
15
20
7
20
25
8
12
15
10
15
10
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