2015 (November)
COMMERCE
(General/Speciality)
Course: 303
(Business Statistics)
The figures in the margin indicate full marks for the questions
(New Course)
Full Marks: 80
Pass Marks: 24
Time: 3 hours
1. Answer any eight questions: 2x8=16
 What do you mean by frequency of a class interval?
 Define a discrete variable.
 Ifbe the mean ofseries, the mean ofseries and, then show that.
 The coefficient of rank correlation betweenpairs of observations isand the sum of the squares of differences between the ranks is, then what will be the value of
 Is it possible for two regression equations to beandExplain, with reason, why?
 What do you mean by cost of living index number?
 What do you mean by ‘base year’ in the construction of index numbers?
 The trend equation for publicity cost (in ‘000 Rs.) of a company is given by (Origin 1st July, 2005, ). Shift the origin to 1st July, 2012.
 Name the components of a time series.
 Write the differences between Laspeyres’ and Paasche’s indices.
 Given the annual trend line equation of production of a company as
2. (a) (i) Prove that for any two values. When do they become equal? 3
(ii) The mean and standard deviation of 100 observations are 50 and 5, and that of another 150 observations are 40 and 6 respectively. Find the combined standard deviation of this 250 observations. 5
(iii) Calculate the coefficient of standard deviation for the following data: 8
Marks: (less than)

80

70

60

50

40

30

20

10

No. of students

100

90

80

60

32

20

13

5

Or
(b) (i)Prove that for a variable, the sum of deviations of the observed values from their arithmetic mean is zero. 3
(ii) Find the mean daily wages from the following data: 5
Wages (Rs.)

230240

240250

250260

260270

270280

280290

No. of workers

8

20

40

18

10

4

(iii) Give the definition of semiinterquartile range. Mention one merit and one demerit of. 3
(iv) Why is standard deviation considered to be the best measure of dispersion? Explain. 5
3. (a) (i) State the properties of Karl Pearson’s coefficient of correlation. 3
(ii) What do you mean by regression lines? Explain why there should be two lines of regression. 5
(iii) Calculate Karl Pearson’s coefficient of correlation from the given data: 8
X:

35

42

20

50

72

64

Y:

40

48

24

60

84

68

Or
(b) (i) Discuss the uses of regression equations. 3
(ii) Calculate the coefficient of rank correlation from the data given below: 5
SL. No.

1

2

3

4

5

6

7

8

9

10

X:

48

33

40

9

16

65

24

18

44

20

Y:

13

10

24

6

15

4

20

9

10

19

(iii) Derive the equations of two regression lines for the following data: 8
X:

35

42

20

50

72

64

Y:

40

48

24

60

84

68

4. (a) (i) What are the different types of index numbers? Name each of them. 3
(ii) Calculate CLI from the given data: 5
Group

Index No.

Weight

Clothing

360

60

Food

298

5

Fuel and Lighting

287

7

House Rent

110

8

Miscellaneous

315

20

(iii) Using the following data prove that Fisher’s index number satisfy (1) time reversal test and (2) factor reversal test: 8
Commodity

Base Year

Current Year
 
Price (in Rs.)

Quantity.

Price (in Rs.)

Quantity
 
A
B
C
D
E

4
5
2
1
3

20
15
30
50
25

6
6
3
1
5

18
12
30
60
28

Or
(b) (i) The monthly salary of an employee in the year 2010 was Rs. 18,500 and then the cost of living index was 160. In the year 2012 the cost of living index became 200. What should be the monthly salary of the employee in the year 2012 to rightly compensate him for price rise?
(ii) Discuss the limitations of index numbers.
(iv) What is Laspeyres’ price index number? Using the following data, show that Laspeyer’s formula does not satisfy the time reversal test: 8
Commodity

Base Year

Current Year
 
Price (in Rs.)

Quantity.

Price (in Rs.)

Quantity
 
A
B
C
D
E

6
2
4
10
8

50
100
60
30
40

10
2
6
12
12

56
120
60
24
36

5. (a) (i) Write the two mathematical models used for analysis of timeseries data. 3
(ii) Calculate the trend value by using 3 yearly moving averages for the following data: 5
Year:

2008

2009

2010

2011

2012

2013

Production:

77

88

94

85

91

98

(iii) Fit a straight line trend for the following data and estimate the production for the year 2010: 8
Year:

2002

2003

2004

2005

2006

2007

2008

Production (‘000 ton):

200

225

175

165

200

265

285

Or
(b) (i) What do you mean by seasonal variations? What are the uses of studying it? 3
(ii) Calculate 3 yearly weighted moving average with weights 2, 2, 1, 2, 2, 1, 2 for the following data: 5
Year:

1995

1996

1997

1998

1999

2000

2001

Value:

45

43

47

49

46

45

42

(iii) Using the method of simple averages, calculate the seasonal indices for the following data: 8
Quarter

2010

2011

2012

I

72

74

84

II

50

68

60

III

78

74

62

IV

92

90

76

(Old Course)
Full Marks: 80
Pass Marks: 32
Time: 3 hours
The figures in the margin indicate full marks for the questions
1. (a) (i) Prove that the sum of the variate values from their arithmetic mean is zero. 2
(ii) If mean and mode of a moderately skewed distribution are 36.4 and 34.6 respectively, find its median. 3
(iii) What is standard deviation? Why is it regarded as the best measure of dispersion? 4
(iv) If arithmetic mean of the following distribution is 72.5, find the missing frequency and also calculate the mode for the distribution: 4+3=7
Marks:

3039

4049

5059

6069

7079

8089

9099

No. of students:

2

3

11

20



25

7

Or
(b) (i) Discuss about the relationship between mean, median and mode. 2
(ii) Calculate the mode and median for the following data: 3
6, 4, 3, 6, 5, 3, 3, 2, 4, 3, 4, 3, 3, 4, 3, 4, 2, 2, 4, 3, 5, 4, 3, 4, 3, 3, 4, 1, 2, 3.
(iii) Calculate the coefficient of quartile deviation for the following data: 4
Wages (Rs.):

5862

6266

6670

7074

7478

7882

8286

No. of Persons

4

7

11

16

12

8

2

(iv) Calculate the standard deviation for the following distribution: 7
Marks (more than):

0

10

20

30

40

50

60

No. of students:

80

77

72

68

53

40

0

2. (a) (i) Prove that, coefficient of correlation is the geometric mean of the two regression coefficients. 2
(ii) Find the value offrom the following data: 3
anddenotes the derivations ofandseries from their AM. 3
(iii) What do you mean by regression lines? Explain why there should be two lines of regression. 4
(iv) Find the appropriate regression equation from the data given below: 7
Age:

56

42

72

36

63

47

55

49

38

Blood Pressure:

147

125

160

118

149

128

150

145

115

Or
(b) (i) What are the properties of two regression coefficients? 2
(ii) If two regression equations are andfind the values ofand. 3
(iii) From the following data, find the two regression equations: 4
X

Y
 
Arithmetic Mean
Standard Deviation

20
5

25
4

Correlation coefficient 0.6
(iv) Calculate the value of coefficient of correlation from the following data: 7
X:

43

44

46

40

44

42

45

42

38

40

Y:

29

31

19

18

19

27

27

29

41

30

3. (a) (i) “The wholesale price index of the year 2015 taking 2010 as base year is 165.” What information can you derive from this statement about the rise in wholesale prices? 2
(ii) Write a short note on factor reversal test. 3
(iii) Calculate the cost of living index number from the following data: 4
Commodity

Weight

Index

Food

50

241

Clothing

2

221

Fuel

3

204

House Rent

16

256

Others

29

179

(iv) Calculate Fisher’s price index number from the data given below: 7
Commodity

Base Year

Current Year
 
Price (in Rs.)

Quantity.

Price (in Rs.)

Quantity
 
A
B
C
D
E

25
20
30
12
90

30
22
54
20
15

30
22
33
15
19

35
25
64
25
18

Or
(b) (i) Write the differences between chain base and fixed base index numbers. 2
(ii) What are ‘weights’ in the construction of index numbers? Discuss the importance of weights. 3
(iii) Discuss the limitations of index numbers. 4
(iv) Calculate Fisher’s index from the data given below, and hence prove that Fisher’s index number satisfies factor reversal test: 7
Commodity

Base Year

Current Year
 
Price (in Rs.)

Quantity.

Price (in Rs.)

Quantity
 
A
B
C
D
E

5
3
4
11
7

50
100
60
30
40

10
4
6
14
10

56
120
60
24
36

4. (a) (i) Write the two mathematical models used for the analysis of time series data. 2
(ii) Write a short note about the uses of studying time series. 3
(iii) Calculate 3 yearly moving averages from the data given below: 4
Year:

1

2

3

4

5

6

7

8

9

Value:

150

200

225

175

165

200

265

285

350

(iv) Using the principle of least squares, calculate the trend line equation for the data given below: 7
Year:

1985

1986

1987

1988

1989

1990

1991

Production:

23

20

18

18

14

13

13

Or
(b) (i) Given the annual trend equationWhat is its monthly trend equation? 2
(ii) In a multiplicative model of time series analysis T = 100, S = 1.2, C = 1.04 and I = 0.9, find the value of y. 3
(iii) Discuss the limitations of time series analysis. 4
(iv) Using the method of 4 yearly moving averages, calculate the trend values for the following data: 7
Year:

1

2

3

4

5

6

7

8

9

10

Price:

20

21

23

22

25

24

27

26

28

30

5. (a) (i) What do you mean by business forecasting? 2
(ii) Write the differences between forecasting and estimation. 3
(iii) Discuss the assumptions of forecasting. 4
(iv) Write short notes on sales forecasting and demand forecasting. 7
Or
(b) (i) Discuss the uses of extrapolation as a method of forecasting. 2
(ii) What precautions are to be taken while forecasting? 3
(iii) Discuss the limitations of forecasting. 4
(iv) Discuss how regression analysis may be used for forecasting. 7