Schmeckt Gut: Economic Principles, Decision Making & Market Analysis

This report delves into the economic principles and decision-making processes surrounding Schmeckt Gut's planned market launch of the Schmeckt Besser energy bar in Atollia. It utilizes market analysis data provided by Schmeckt Gut's research department, focusing on scenarios involving varying income growth, inflation rates, and tariff rates on imports. The analysis employs a quantitative multiple regression approach to assess the sensitivity of product demand to changes in external economic variables. The report examines the relationship between macroeconomic indicators like income growth, inflation, and tariff rates, and their impact on the aggregate demand and supply. Furthermore, based on the regression analysis results, the report provides recommendations for Schmeckt Gut's management, considering different economic scenarios and their potential effects on the demand for the energy bar. The regression results highlight the significant influence of real income and tariffs on product demand, while the number of stores has a less significant impact. The report concludes with tailored strategies based on the projected economic conditions.

1
ECONOMICS PRINCIPLE AND DECISION MAKING

2
Executive summary
Decision making is crucial for any kind of business and market analysis works as a resource
for the process. Schmeckt Gut carries out market analysis and collects data based on the
demand for the product. The study in the paper uses the multiple regression analysis to find
out the effect of the dependent variable on the dependent variable. Furthermore, based on the
study and the relationship between the economic variables, the paper also presents
recommendations for the management of Schmeckt Gut.

3
Table of contents
1.0 Introduction..........................................................................................................................4
2.0 Methods................................................................................................................................4
3.0 Discussions...........................................................................................................................4
3.1 Relationship between the different projections....................................................................4
3.2 Impact on the demand for the product of the company.......................................................5
3.3 Recommendations................................................................................................................7
4.0 Conclusion............................................................................................................................9
Reference..................................................................................................................................10

4
1.0 Introduction
Decision making is one of the important functions of any organisation. The decision making
becomes more crucial in the case of B2C businesses where the customers are the consumers
of the end products. There are few resources which are required for a company to make
decisions such as market analysis, survey and many more. In this study, Schmeckt Gut is a
company that wants to introduce its energy bar product in the market. Using its marketing
analysis result, this paper aims to discuss the impacts of the different economic variable on
the demand of the product. Based on that, the study carried out in the paper also presents
recommendations based on different situations.
2.0 Methods
The study carried out in the paper uses the data given by the marketing department of
Schmeckt Gut and the secondary data and information collected from other similar papers. A
quantitative multiple regression analysis has been carried out in the paper to arrive at the
result which shows the sensitivity of the demand of the product to the changes in the external
scenarios.
3.0 Discussions
3.1 Relationship between the different projections
The income growth and inflation are two of the most important macroeconomic indicators
that measure the performance of an economy. On the other hand, a tariff rate is a tool used by
the government in order to regulate the domestic market. Karlan (2017) stated that, lowered
tariff rate makes it easier for the foreign company to invade a domestic market which in turn
becomes a trouble for the indigenous businesses.
However, all the three values are dependent on each other. The direct relationship between
the income growth and the inflation rate is justified by the theory of demand and supply. As
the income grows at the rate of 1%, the consumers will demand more products from the
market and hence the demand curve will shift rightward leading to an increase in the price of
that specific product (Laibson & List, 2015). Now this increase in the price of the product,
over time, contributes to the degrading purchasing power of the consumer and hence the
inflation. Corresponding to a 1% increase in the income can result in either of inflation rate as

5
the amount of increase in the price level will depend on the elasticity of that specific product.
If the income elasticity of the demand for a specific product is less than one then the
percentage of increase in price will be less than the percentage increase in the income
(Schansberg, 2016).
Figure 1: The relationship of income and inflation
(Source: Wu & Cheng, 2015)
Again, from the perspective of the economy as a whole and considering all the products of
the market, the increase in the income shifts the aggregate demand to the right side causing
an increase in the price level. Consequently the inflation level increases with the increase in
the income. Bober (2016) commented that, increase in income not only increases the demand
for a single product of the market, but it affects the overall basket of goods and services.
Again, the aggregate demand can also explain the relationship between the inflation rate of
the market and the tariff as well. High tariff rate protects the domestic companies from the
invasion of the foreign businesses (Kagundu, & Ross, 2015). Therefore, domestic companies
get the opportunity to make the most of the increased income of the customers in the market.
The customers with their higher income will demand more domestic goods than the foreign

6
goods. Due to a high Net export component of the aggregate demand, the curve will shift to
the right increasing overall price of the goods and the services of the economy (Friedman,
2018). That means a 10% tariff rate can increase the inflation of the economy to 5%.
Figure 2: The changes in the aggregate demand and price
(Source: Kagundu, & Ross, 2015)
However, the aggregate supply of the economy is not directly related to the changes in the
income (Wu & Cheng, 2015). However, there exists a relation between the unemployment
rate and the wage rates in the labour market. Thus, the Phillips curve depicts the relationship
between the level of the unemployment rate and the inflation in the economy. Walstad &
Miller (2016) commented that, the demand curve in the labour market is downward sloping
and hence the rightward shift in the demand curve corresponding to increase in the
employment opportunity increases the equilibrium wage rate of the market (Hussen, 2018).

7
Figure 3: Phillips curve
(Source: Hussen, 2018)
Lastly, the laffers curve shows the relationship between the amount of tax rate and total tax
revenue collected by the government. Gwartney, Stroup, Lee, Ferrarini & Calhoun (2016)
noted that, the government can increase the tax rate in order to increase the overall tax
revenue of the state. However, there is a limitation to the increase in the tax rate, as with
higher taxes, people will be discouraged to work. After a specific point, a higher tax reduces
the tax revenue of the government (Aljamal, Cader, Chiemeke & Speece, 2015). This is due
to the fact that, with high taxes the production of the economies goes down resulting in
deflation and stagnation in the economy.

8
Figure 4: The laffer curve
(Source: Olsen, 2017)
3.2 Impact on the demand for the product of the company
Part 1: Log transformation
Scenario 1: 1% income increase, 2% inflation and 7.5% tariff increase
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.921985
R Square 0.850056
Adjusted R Square0.77784
Standard Error0.085691
Observations 21
ANOVA
df SS MS F Significance F
Regression 3 0.749315 0.249772 51.02237 1.03E-08
Residual 18 0.132174 0.007343
Total 21 0.881489
CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept -9.85029 1.442556 -6.82836 2.16E-06 -12.881 -6.81959 -12.881 -6.81959
Log real income1.571907 0.155929 10.08095 7.89E-09 1.244314 1.899501 1.244314 1.899501
Log tariff -0.50688 0.08357 -6.06539 9.86E-06 -0.68245 -0.33131 -0.68245 -0.33131
Log number of stores0 0 65535 #NUM! 0 0 0 0

9
Table 1: The regression analysis of scenario 1
In this case the r square value is 0.85 which is a good fit and the variable of real income has
the most influence on the demand for the product.
Scenario 2: 2% income increase 3% inflation and 5% tariff increase
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.915519119
R Square 0.838175258
Adjusted R Square 0.764639176
Standard Error 0.089021451
Observations 21
ANOVA
df SS MS F Significance F
Regression 3 0.738842316 0.246280772 46.61572285 2.04509E-08
Residual 18 0.142646739 0.007924819
Total 21 0.881489055
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -9.694971005 1.493158038 -6.49293026 4.17272E-06 -12.83197963 -6.55796238 -12.83197963 -6.55796238
X Variable 1 1.547035837 0.160539405 9.636486665 1.57412E-08 1.209755063 1.884316611 1.209755063 1.884316611
X Variable 2 -0.496648482 0.086762919 -5.724202052 1.99222E-05 -0.678930611 -0.314366352 -0.678930611 -0.314366352
X Variable 3 0 0 65535 #NUM! 0 0 0 0
Table 2: The regression analysis for the scenario 2
This scenario has the goodness of fit of 0.83 which is a good measure and the real income has
the huge influence over the demand for the product.
Scenario 3: 5% income increase, 5% inflation and 5% tariff increase
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.933159874
R Square 0.87078735
Adjusted R Square 0.800874833
Standard Error 0.079547169
Observations 21
ANOVA
df SS MS F Significance F
Regression 3 0.767589518 0.255863173 60.65262309 2.73954E-09
Residual 18 0.113899537 0.006327752
Total 21 0.881489055
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -10.28813855 1.362793123 -7.549303249 5.54069E-07 -13.15126065 -7.425016447 -13.15126065 -7.425016447
X Variable 1 1.614191023 0.146854671 10.9917581 2.04488E-09 1.305660808 1.922721239 1.305660808 1.922721239
X Variable 2 -0.512715672 0.077528115 -6.613286946 3.29004E-06 -0.675596198 -0.349835147 -0.675596198 -0.349835147
X Variable 3 0 0 65535 #NUM! 0 0 0 0

10
Figure 3: The regression analysis for the scenario 3
The r squared value for this analysis is 0.87 which says that the independent variables
explains 87% of the changes in the demand for the product.
Scenario 4: 5% income increase, 5% inflation and 0% tariff change
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.921984758
R Square 0.850055895
Adjusted R Square 0.777839883
Standard Error 0.085691335
Observations 21
ANOVA
df SS MS F Significance F
Regression 3 0.749314967 0.249771656 51.02236615 1.03228E-08
Residual 18 0.132174088 0.007343005
Total 21 0.881489055
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -9.902431361 1.447600385 -6.840583537 2.11151E-06 -12.94372691 -6.861135812 -12.94372691 -6.861135812
X Variable 1 1.571907356 0.155928538 10.08094719 7.88772E-09 1.244313655 1.899501058 1.244313655 1.899501058
X Variable 2 -0.50688151 0.083569536 -6.065386168 9.86019E-06 -0.68245459 -0.331308429 -0.68245459 -0.331308429
X Variable 3 0 0 65535 #NUM! 0 0 0 0
Table 4: The regression analysis for the scenario 4
The R squared value of this analysis is 0.85 and the impact of the real income is the most on
the demand for the product.
Part 2: The regression analysis is presented below:
SUMMARY
OUTPUT
Regression Statistics
Multiple R
0.9147
57
R Square
0.8367
8
Adjusted R
Square
0.8306
59
Standard
Error
0.0848
17
Observation
s 84
ANOVA

11
df SS MS F
Signific
ance F
Regression 3 2.950449
0.983
483
136.7
118
2.14E-
31
Residual 80 0.575507
0.007
194
Total 83 3.525956
Coeffic
ients
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
-
9.5375
9 0.721743
-
13.21
47
8.24
E-22
-
10.9739
-
8.1012
7
-
10.9739
-
8.10127
Log real
income
1.5471
33 0.076553
20.21
008
3.61
E-33
1.39478
8
1.6994
77
1.39478
8
1.69947
7
Log tariff
-
0.4936
1 0.041094
-
12.01
19
1.36
E-19
-
0.57539
-
0.4118
3
-
0.57539
-
0.41183
Log number
of stores
-
0.0452
9 0.054189
-
0.835
71
0.405
809
-
0.15313
0.0625
54
-
0.15313
0.06255
4
Table 1: The regression analysis
(Source: Developed by the learner)
The regression analysis shows how the independent variables explain and influences the
changes in the dependant variable Oliver & Lundquist,2017). In this case, the dependant
variable is the Log Demand which depends on the value of the variables such as Log real
income, Log tariff and log number of stores.
The R square value of the analysis is 0.83 which means the independent variables explains
83% of the changes in the demand for the product (Olsen, 2017). The result shows that,
income has the coefficient of 1.54 which means 1 unit change in the income the demand
increases by 1.54 Unit. Again the log tariff has the coefficient of -0.49 which means 1 unit
increase in the tariff decerases the demand by 0.49 units. Lastly, The number of stores have
the least significant impact on the demand for the product of Schmeckt Gut.
Scenario 1: 1% income increase, 2% inflation and 7.5% tariff increase
Income increases only by 1% and hence increase in demand is low. Given the high tariff the
supply is also low in this case.

12
Figure 5: Change in price for scenario 1
Scenario 2: 2% income increase 3% inflation and 5% tariff increase
In this scenario, the gap between the income increase and inflation is same however the tariff
has reduced resulting in more stores in the market. Therefore the price mostly remains the
same and the quantity increases.
Figure 6: Change in price for scenario 2
Scenario 3: 5% income increase, 5% inflation and 5% tariff increase
In this scenario the real income increase is marginal and the increase in supply is more due to
the reduction in tariff. Thus the price reduces.

13
Figure 7: The change in price in scenario 3
Scenario 4: 5% income increase, 5% inflation and 0% tariff change
The scenario 4 shows the free trade case where the real income is same as before. The tariff is
low and hence the supply is the maximum leading to the most reduction in price and hence
increases in real income.
Figure 8: The change in price in case of scenario 4
3.3 Recommendations
Scenario 1: Income growth 1%, Inflation 2% and tariff 7.5%
In this case the income growth rate is less than the inflation rate of the economy. That means
the change in the income will hardly have any effect on the demand for the energy bar of
Schmeckt Gut. Apart from that the demand for the product will also below in this case
(Friedman, 2017). For this situation it is recommended for the management of Schmeckt Gut
to reduce the prices of the products. The reduced prices of the product will increase the real

14
income of the consumer and hence the demand for the product will start to rise. Thus, in this
case, a competitive price strategy for the products will be useful.
Scenario 2: Income growth 2% inflation 3% and tariff 5%
In this scenario the income growth of the consumer is more than the inflation rate of the
economy. That means the real income increase is positive, which can have a positive impact
on the demand for the product (Vasigh & Fleming, 2016). The tariff in this case is also low
which can have a positive impact on the demand for the product. In this scenario it is
recommended for the management of the company is to increase the number of stores in the
market. The increased number of stores will help in the promotion of the products and hence
the demand will increase. The above regression analysis also shows that the number of stores
positively influences the demand for the energy bars of Schmeckt Gut.
Scenario 3: Income growth 5%, inflation 5% and free trade
The free trade in this case ensures the demand for the product is the highest. The regression
analysis shows that the demand of the product is negatively related to the tariff rate. In this
case the low tariff rate or the free trade paves the way for a high demand for the product. In
addition to that, in this scenario, the income growth rate is also more than the inflation rate in
the economy (Stiglitz & Rosengard, 2015). That means the real income of the consumers of
the market is also very high. Therefore, it is recommended for the management of Schmeckt
Gut to use a premium price for the energy bars of the company. It needs to be that due to the
fact that the energy bar is inelastic, the higher price will enable the company to earn increased
revenue.
Scenario 4: Income growth 5%, inflation 5% and tariff 5 %
This is a situation where the inflation of the economy is similar to the increase in the wage of
the consumers of the market. Therefore, the real income of the consumers remains intact over
the time. Moreover the moderate tariff rate on the import of the energy bar also justifies the
low demand for the product. Therefore, in this scenario, it is recommended for the
management of Schmeckt Gut to keep constant prices for the energy bar product of the
company for a long period of time. Any kinds of increase in price may result in loss of
customer or any kind of decrease in price may result in a decrease in the revenue of the
company.

15
4.0 Conclusion
Therefore the paper carries out the study regarding the variables of the model. It shows that,
theories of demand and supply, aggregate demand justifies the changes in the income and the
prices of the products in the economy. The regression analysis carried out in the paper also
shows that, while the higher number of stores may increase the demand for the product, the
increase in the tariff rate would result in the decline in the demand for the product. Lastly the
paper concludes with the recommendations based on the different situations.

16
Reference
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learning on performance in principles of economics. International Review of
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Bober, S. (2016). Alternative principles of economics. Routledge.
Friedman, G. (2018). Book Review: What Every Economics Student Needs to Know, and
Doesn’t Get in the Usual Principles Text.
Friedman, M. (2017). Price theory. Routledge.
Gwartney, J. D., Stroup, R., Lee, D., FERRARINI, T. H., & Calhoun, J. (2016). Common
Sense Economics: What Everyone Should Know about Wealth and Prosperity (2016)
Hussen, A. (2018). Principles of environmental economics and sustainability: an integrated
economic and ecological approach. Routledge.
Kagundu, P., & Ross, G. (2015). The impact of question order on multiple choice exams on
student performance in an unconventional introductory economics course. Journal for
Economic Educators, (1), 19-36.
Karlan, D. S. (2017). DP12015 Survivor: Three Principles of Economics Lessons as Taught
by a Reality Television Show.
Laibson, D., & List, J. A. (2015). Principles of (behavioral) economics. American Economic
Review, 105(5), 385-90.
Oliver, H. V., & Lundquist, K. M. (2017). Evaluation of the Prerequisite Requirements in
Principles of Economics and Student Success at Linfield College.
Olsen, J. A. (2017). Principles in health economics and policy. Oxford University Press.
Schansberg, D. E. (2016). TEACHING MICRO AND MACRO IN ALL PRINCIPLES
COURSES. Journal of Economics & Economic Education Research, 17(1).
Stiglitz, J. E., & Rosengard, J. K. (2015). Economics of the public sector: Fourth
international student edition. WW Norton & Company.

17
Vasigh, B., & Fleming, K. (2016). Introduction to air transport economics: from theory to
applications. Routledge.
Walstad, W. B., & Miller, L. A. (2016). What's in a grade? Grading policies and practices in
principles of economics. The Journal of Economic Education, 47(4), 338-350.
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Interactive Homework System--A Case Study in Teaching Economics At Alabama
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253.

18
Appendix
1) The log transformation
Ann
ual
aver
age
dem
and
of
ener
gy
bars
per
pers
on
Aver
age
inco
me
per
pers
on
Tari
ff
rate
on
imp
orts
of
ener
gy
bars
Num
ber
of
stor
es
whe
re
ener
gy
bars
are
offer
ed
Infla
tion
Incra
sed
inco
me
Real
inco
me
Ne
w
tari
ff
Num
ber
of
stor
es
Log
dema
nd
Log
real
inco
me
Log
tariff
Log
num
ber
of
store
s
106
1550
0 5 15 2%
1565
5
1534
8.04
5.3
75 15
4.663
439
9.638
743
1.681
759
2.708
05
90
1581
0 5 15 2%
1596
8.1
1565
5
5.3
75 15
4.499
81
9.658
546
1.681
759
2.708
05
93
1639
5 5 15 2%
1655
9
1623
4.26
5.3
75 15
4.532
599
9.694
879
1.681
759
2.708
05
92
1688
7 5 15 2%
1705
5.9
1672
1.44
5.3
75 15
4.521
789
9.724
447
1.681
759
2.708
05
91
1749
5 5 15 2%
1767
0
1732
3.48
5.3
75 15
4.510
86
9.759
818
1.681
759
2.708
05
110
1828
2 5 16 2%
1846
4.8
1810
2.76
5.3
75 15
4.700
48
9.803
82
1.681
759
2.708
05
109
1901
3 5 16 2%
1920
3.1
1882
6.6
5.3
75 15
4.691
348
9.843
026
1.681
759
2.708
05
122
1950
8 5 16 2%
1970
3.1
1931
6.75
5.3
75 15
4.804
021
9.868
728
1.681
759
2.708
05
82
1989
8 10 16 2%
2009
7
1970
2.92
10.
75 15
4.406
719
9.888
522
2.374
906
2.708
05
84
2027
6 10 16 2%
2047
8.8
2007
7.22
10.
75 15
4.430
817
9.907
341
2.374
906
2.708
05
102
2070
2 10 17 2%
2090
9
2049
9.04
10.
75 15
4.624
973
9.928
133
2.374
906
2.708
05
92
2155
0 10 17 2%
2176
5.5
2133
8.73
10.
75 15
4.521
789
9.968
279
2.374
906
2.708
05
115
2219
7 10 20 2%
2241
9
2197
9.38
10.
75 15
4.744
932
9.997
86
2.374
906
2.708
05
112
2233
0 10 20 2%
2255
3.3
2211
1.08
10.
75 15
4.718
499
10.00
383
2.374
906
2.708
05
109
2275
4 10 20 2%
2298
1.5
2253
0.92
10.
75 15
4.691
348
10.02
264
2.374
906
2.708
05
148
2361
9 7.5 20 2%
2385
5.2
2338
7.44
8.0
625 15
4.997
212
10.05
995
2.087
224
2.708
05

19
143
2385
5 7.5 20 2%
2409
3.6
2362
1.13
8.0
625 15
4.962
845
10.06
99
2.087
224
2.708
05
139
2445
2 7.5 20 2%
2469
6.5
2421
2.27
8.0
625 15
4.934
474
10.09
461
2.087
224
2.708
05
158
2494
1 7.5 23 2%
2519
0.4
2469
6.48
8.0
625 15
5.062
595
10.11
442
2.087
224
2.708
05
142
2551
4 7.5 23 2%
2576
9.1
2526
3.86
8.0
625 15
4.955
827
10.13
713
2.087
224
2.708
05
158
2594
8 7.5 23 2%
2620
7.5
2569
3.61
8.0
625 15
5.062
595
10.15
4
2.087
224
2.708
05
106
1550
0 5 15 3%
1627
5
1595
5.88 5.5 16
4.663
439
9.677
583
1.704
748
2.772
589
90
1581
0 5 15 3%
1660
0.5
1627
5
5.2
5 16
4.499
81
9.697
385
1.658
228
2.772
589
93
1639
5 5 15 3%
1721
4.8
1687
7.21
5.2
5 16
4.532
599
9.733
719
1.658
228
2.772
589
92
1688
7 5 15 3%
1773
1.4
1738
3.68
5.2
5 16
4.521
789
9.763
287
1.658
228
2.772
589
91
1749
5 5 15 3%
1836
9.8
1800
9.56
5.2
5 16
4.510
86
9.798
658
1.658
228
2.772
589
110
1828
2 5 16 3%
1919
6.1
1881
9.71
5.2
5 16
4.700
48
9.842
66
1.658
228
2.772
589
109
1901
3 5 16 3%
1996
3.7
1957
2.21
5.2
5 16
4.691
348
9.881
866
1.658
228
2.772
589
122
1950
8 5 16 3%
2048
3.4
2008
1.76
5.2
5 16
4.804
021
9.907
567
1.658
228
2.772
589
82
1989
8 10 16 3%
2089
2.9
2048
3.24
10.
5 16
4.406
719
9.927
362
2.351
375
2.772
589
84
2027
6 10 16 3%
2128
9.8
2087
2.35
10.
5 16
4.430
817
9.946
181
2.351
375
2.772
589
102
2070
2 10 17 3%
2173
7.1
2131
0.88
10.
5 16
4.624
973
9.966
973
2.351
375
2.772
589
92
2155
0 10 17 3%
2262
7.5
2218
3.82
10.
5 16
4.521
789
10.00
712
2.351
375
2.772
589
115
2219
7 10 20 3%
2330
6.9
2284
9.85
10.
5 16
4.744
932
10.03
67
2.351
375
2.772
589
112
2233
0 10 20 3%
2344
6.5
2298
6.76
10.
5 16
4.718
499
10.04
267
2.351
375
2.772
589
109
2275
4 10 20 3%
2389
1.7
2342
3.24
10.
5 16
4.691
348
10.06
148
2.351
375
2.772
589
148
2361
9 7.5 20 3%
2480
0
2431
3.68
7.8
75 16
4.997
212
10.09
879
2.063
693
2.772
589
143
2385
5 7.5 20 3%
2504
7.8
2455
6.62
7.8
75 16
4.962
845
10.10
874
2.063
693
2.772
589
139
2445
2 7.5 20 3%
2567
4.6
2517
1.18
7.8
75 16
4.934
474
10.13
345
2.063
693
2.772
589
158
2494
1 7.5 23 3%
2618
8.1
2567
4.56
7.8
75 16
5.062
595
10.15
326
2.063
693
2.772
589
142
2551
4 7.5 23 3%
2678
9.7
2626
4.41
7.8
75 16
4.955
827
10.17
597
2.063
693
2.772
589

20
158
2594
8 7.5 23 3%
2724
5.4
2671
1.18
7.8
75 16
5.062
595
10.19
284
2.063
693
2.772
589
106
1550
0 5 15 5%
1627
5
1595
5.88
5.2
5 20
4.663
439
9.677
583
1.658
228
2.995
732
90
1581
0 5 15 5%
1660
0.5
1581
0
5.2
5 20
4.499
81
9.668
398
1.658
228
2.995
732
93
1639
5 5 15 5%
1721
4.8
1639
5
5.2
5 20
4.532
599
9.704
732
1.658
228
2.995
732
92
1688
7 5 15 5%
1773
1.4
1688
7
5.2
5 20
4.521
789
9.734
299
1.658
228
2.995
732
91
1749
5 5 15 5%
1836
9.8
1749
5
5.2
5 20
4.510
86
9.769
67
1.658
228
2.995
732
110
1828
2 5 16 5%
1919
6.1
1828
2
5.2
5 20
4.700
48
9.813
672
1.658
228
2.995
732
109
1901
3 5 16 5%
1996
3.7
1901
3
5.2
5 20
4.691
348
9.852
878
1.658
228
2.995
732
122
1950
8 5 16 5%
2048
3.4
1950
8
5.2
5 20
4.804
021
9.878
58
1.658
228
2.995
732
82
1989
8 10 16 5%
2089
2.9
1989
8
10.
5 20
4.406
719
9.898
375
2.351
375
2.995
732
84
2027
6 10 16 5%
2128
9.8
2027
6
10.
5 20
4.430
817
9.917
193
2.351
375
2.995
732
102
2070
2 10 17 5%
2173
7.1
2070
2
10.
5 20
4.624
973
9.937
986
2.351
375
2.995
732
92
2155
0 10 17 5%
2262
7.5
2155
0
10.
5 20
4.521
789
9.978
131
2.351
375
2.995
732
115
2219
7 10 20 5%
2330
6.9
2219
7
10.
5 20
4.744
932
10.00
771
2.351
375
2.995
732
112
2233
0 10 20 5%
2344
6.5
2233
0
10.
5 20
4.718
499
10.01
369
2.351
375
2.995
732
109
2275
4 10 20 5%
2389
1.7
2275
4
10.
5 20
4.691
348
10.03
25
2.351
375
2.995
732
148
2361
9 7.5 20 5%
2480
0
2361
9
7.8
75 20
4.997
212
10.06
981
2.063
693
2.995
732
143
2385
5 7.5 20 5%
2504
7.8
2385
5
7.8
75 20
4.962
845
10.07
975
2.063
693
2.995
732
139
2445
2 7.5 20 5%
2567
4.6
2445
2
7.8
75 20
4.934
474
10.10
447
2.063
693
2.995
732
158
2494
1 7.5 23 5%
2618
8.1
2494
1
7.8
75 20
5.062
595
10.12
427
2.063
693
2.995
732
142
2551
4 7.5 23 5%
2678
9.7
2551
4
7.8
75 20
4.955
827
10.14
698
2.063
693
2.995
732
158
2594
8 7.5 23 5%
2724
5.4
2594
8
7.8
75 20
5.062
595
10.16
385
2.063
693
2.995
732
106
1550
0 5 15 5%
1627
5
1550
0 5 23
4.663
439
9.648
595
1.609
438
3.135
494
90
1581
0 5 15 5%
1660
0.5
1581
0 5 23
4.499
81
9.668
398
1.609
438
3.135
494
93
1639
5 5 15 5%
1721
4.8
1639
5 5 23
4.532
599
9.704
732
1.609
438
3.135
494

21
92
1688
7 5 15 5%
1773
1.4
1688
7 5 23
4.521
789
9.734
299
1.609
438
3.135
494
91
1749
5 5 15 5%
1836
9.8
1749
5 5 23
4.510
86
9.769
67
1.609
438
3.135
494
110
1828
2 5 16 5%
1919
6.1
1828
2 5 23
4.700
48
9.813
672
1.609
438
3.135
494
109
1901
3 5 16 5%
1996
3.7
1901
3 5 23
4.691
348
9.852
878
1.609
438
3.135
494
122
1950
8 5 16 5%
2048
3.4
1950
8 5 23
4.804
021
9.878
58
1.609
438
3.135
494
82
1989
8 10 16 5%
2089
2.9
1989
8 10 23
4.406
719
9.898
375
2.302
585
3.135
494
84
2027
6 10 16 5%
2128
9.8
2027
6 10 23
4.430
817
9.917
193
2.302
585
3.135
494
102
2070
2 10 17 5%
2173
7.1
2070
2 10 23
4.624
973
9.937
986
2.302
585
3.135
494
92
2155
0 10 17 5%
2262
7.5
2155
0 10 23
4.521
789
9.978
131
2.302
585
3.135
494
115
2219
7 10 20 5%
2330
6.9
2219
7 10 23
4.744
932
10.00
771
2.302
585
3.135
494
112
2233
0 10 20 5%
2344
6.5
2233
0 10 23
4.718
499
10.01
369
2.302
585
3.135
494
109
2275
4 10 20 5%
2389
1.7
2275
4 10 23
4.691
348
10.03
25
2.302
585
3.135
494
148
2361
9 7.5 20 5%
2480
0
2361
9 7.5 23
4.997
212
10.06
981
2.014
903
3.135
494
143
2385
5 7.5 20 5%
2504
7.8
2385
5 7.5 23
4.962
845
10.07
975
2.014
903
3.135
494
139
2445
2 7.5 20 5%
2567
4.6
2445
2 7.5 23
4.934
474
10.10
447
2.014
903
3.135
494
158
2494
1 7.5 23 5%
2618
8.1
2494
1 7.5 23
5.062
595
10.12
427
2.014
903
3.135
494
142
2551
4 7.5 23 5%
2678
9.7
2551
4 7.5 23
4.955
827
10.14
698
2.014
903
3.135
494
158
2594
8 7.5 23 5%
2724
5.4
2594
8 7.5 23
5.062
595
10.16
385
2.014
903
3.135
494