mis-financial modeling2 dataset

8/22/2019 Mis-financial Modeling2 Dataset

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Data set Two sets of latest data on country debt and in

Purpose Undertand the graphic representation

Analysis required Show the given data in columnar graph

Exercise-2


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vestments


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Debt Stock

Holdings in US Treasury Securities Sl.No. Country 2000 2010

Country Amount($bn) 1 Japan 142.06 220.28

China 1160 2 Greece 103.44 142.02

Japan 912 3 Italy 109.17 119.01

UK 346 4 Ireland 37.76 96.14Oil Exporters 230 5 US 54.84 91.55

Brazil 211 6 France 57.33 84.25

Taiwan 153 7 Canada 82.13 84.04

India 41 8 Portugal 48.48 83.32

Total 3053 9 Germany 59.74 79.99

10 UK 40.97 77.24

Represent the above data in a 11 India 71.44 69.17

column graph 12 Brazil 66.65 66.07

13 Spain 59.26 60.11

14 Taiwan 25.38 39.7115 South Africa 41.96 35.74

16 South Korea 16.73 30.86

17 China 16.45 17.71

18 Russia 59.86 9.87

Gross Debt as a percentage of


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Change in %

DP


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Data set monthwise data on two variables, price and demand

Purpose Undertand the graphic representation of the relationship

and dependent variableCapture the relationship in the form of a mathematical e

Understand Excel's curve fitting capability

Analysis required Show the given data as a scatter graph and fit linear, exp

Which of the three equations is reliabe based on the Mea

Exercise-3


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between independent

uation for forecasting

ential and power curves

n Absolute Error Percentage


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Month Price Demand

1 450 45

2 300 103

3 440 49

4 360 865 290 125

6 450 52

7 340 87

8 370 68

9 500 45

10 490 44

11 430 58

12 390 68


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Data set Monthly material consumption-work order number wise

Purpose Understand the database query commands of Excel

Analysis required Set up a basic query and advanced query model for querytype of data

Exercise-4


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and material code wise

ing and retrieving any


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SL.NO WONO MATCODE QTY RATE VALUE

1 A001 MA121 60 122.50

2 A002 MA122 100 140.75

3 A003 MA121 121 122.50

4 A001 MA123 125 150.20

5 A002 MA124 80 139.606 A001 MA121 70 122.50

7 A003 MA122 60 140.75

8 M001 MA123 50 150.20

9 A004 MA124 40 139.60

10 A004 MA121 30 122.50

11 A001 MA122 20 140.75

12 A002 MA123 100 150.20

13 M001 MA124 120 139.6014 A005 MA121 125 122.50

15 A005 MA122 130 140.75

16 M001 MA123 140 150.20

17 A001 MA124 150 139.60

18 A002 MA123 125 150.20

19 A003 MA124 128 139.60

20 A004 MA122 129 140.75

21 A005 MA121 150 122.50

22 M001 MA123 30 150.20

23 A003 MA122 80 140.75

24 A002 MA124 90 139.60

25 A004 MA121 110 122.50

26 A005 MA122 120 140.75

27 A003 MA123 125 150.20

28 M001 MA124 80 139.60

29 A005 MA121 70 122.50

30 A001 MA122 55 140.7531 A002 MA123 60 150.20

32 A003 MA124 100 139.60

33 M001 MA121 90 122.50

34 A001 MA122 10 140.75

35 A002 MA123 15 150.20


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Data set Monthly material consumption-work order number wise

Purpose Understand the MIS Summary extraction capability of Exc

Analysis required Summarize the database on the basis of work order and

Exercise-4


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and material code wise

el

aterial code


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SL.NO WONO MATCODE QTY RATE VALUE

1 A001 MA121 60 122.50 7350.00

2 A001 MA123 125 150.20 18775.00

3 A001 MA121 70 122.50 8575.00

4 A001 MA122 20 140.75 2815.005 A001 MA124 150 139.60 20940.00

6 A001 MA122 55 140.75 7741.25

7 A001 MA122 10 140.75 1407.50

8 A002 MA122 100 140.75 14075.00

9 A002 MA124 80 139.60 11168.00

10 A002 MA123 100 150.20 15020.00

11 A002 MA123 125 150.20 18775.00

12 A002 MA124 90 139.60 12564.00

13 A002 MA123 60 150.20 9012.00

14 A002 MA123 15 150.20 2253.00

15 A003 MA121 121 122.50 14822.50

16 A003 MA122 60 140.75 8445.00

17 A003 MA124 128 139.60 17868.80

18 A003 MA122 80 140.75 11260.00

19 A003 MA123 125 150.20 18775.00

20 A003 MA124 100 139.60 13960.00

21 A004 MA124 40 139.60 5584.0022 A004 MA121 30 122.50 3675.00

23 A004 MA122 129 140.75 18156.75

24 A004 MA121 110 122.50 13475.00

25 A005 MA121 125 122.50 15312.50

26 A005 MA122 130 140.75 18297.50

27 A005 MA121 150 122.50 18375.00

28 A005 MA122 120 140.75 16890.00

29 A005 MA121 70 122.50 8575.0030 M001 MA123 50 150.20 7510.00

31 M001 MA124 120 139.60 16752.00

32 M001 MA123 140 150.20 21028.00

33 M001 MA123 30 150.20 4506.00

34 M001 MA124 80 139.60 11168.00

35 M001 MA121 90 122.50 11025.00


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WONO VALUE VALUE criteria raA001 >10000


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ge

ge


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Data set Departmentwise Budget and actual Expenditu

Purpose Understand the MIS Process-Budget VS Actual

Analysis required Summarize the database on the basis of depawith the budget, show the results graphically

Exercise-6


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re for a period

ls comparison

rtment and compare the actuals


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Sum of Amount Column Labels

Row Labels A001 A002 A003 A004 Grand Total

Administration 2000 9500 11500

Finance 6000 4000 4000 14000

Personnel 4000 2500 6000 12500Production 8000 5500 13500

Grand Total 20000 16000 10000 5500 51500


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Department Bud. Amount Actual amount

Administration 10000

Finance 9000

Personnel 8000

Production 12000

Department Exp. Code Amount

Administration A001 2000

Personnel A002 2500

Production A001 4000

Finance A001 3000


Personnel A003 2000


Finance A001 3000


Personnel A003 4000


Finance A003 4000


Personnel A001 4000

Production A001 4000Finance A002 4000

mis-financial modeling2 dataset

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