BUS6225 Business Statistics; latest exam questions with 100% correct answers graded A+
Exam (elaborations) BUS6225 Business Statistics
BUS6225 Business Statistics ; latest version of exam questions on business statistics with 100% correct answers graded A+
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Business Statistics HV
Practice Questions
Index Numbers and Time Series
1. Explain various tests of adequacy of Index numbers. Why is Fisher’s Index known as an ideal
index number.
2. Calculate the cost of living index number for the year 2010 on the basis of 2005 from the following data
where a consumer basket consists of 6 commodity groups. If a person was earning Rs 50,000 per month
in 2005 what should have been his salary in 2010
Commodity groups Weights Prices in Prices in
2005 2010
(Rs per unit) (Rs per unit)
A 40 16 20
B 25 40 48
C 5 0.5 0.5
D 20 88 100
E 10 65 80
3. Write a short note explaining BSE SENSEX and NSE NIFTY index numbers.
4. From the following two different index number series, construct a new series of Index number with base
year as 2008
5. For the following data calculate Quantity Index number using (i) Fisher’s method and (ii) Marshall
Edgeworth method.
Commodity Quantity Base year Price base Year Expenditure Quantity Current
Kg Rs Current year year
A 40 25 2000 50
B 18 22 1200 30
, C 16 54 1320 44
D 40 20 1350 45
E 30 18 630 15
Answer (i) 136.85 (ii) 134.94
6. A Company made spent 50, 48,18 and 42 Rs lakh on 4 items in 2012. In the year 2013 the expenditures
increased to 100,98,60 and 102 Rs lakh on these items respectively. If the units purchased of each item is
same in both years respectively, compute the price index of the current year using appropriates method.
What method would you prefer if the quantities are 4 items are given as 5,2,6 and 17 respectively?
Answer : 227.85
7. Fit a linear trend for the following data on annual steel production (in million tons) in a state.
Year Production
1995 23
1996 25
1997 50
1998 45
1999 60
2000 75
2001 84
2002 100
8. Calculate the four seasonal indices for rain fall (in mm) in Karnataka using simple average method
Rainfall in mm
Year Season I Season II Season III Season IV
2005 118 260 379 20
2006 85 185 405 25
2007 95 190 401 22
2008 120 200 400 22
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