Data Analysis Project 3Presented By Yiwen LiNational Ec.docx

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Data Analysis Project 3 Presented By: Yiwen Li National Economy Above graph shows the personal income relation with consumer expenditure. Consumer expenditure is in % as personal income increases consumer expenditure also increases. Increase In Personal Income Increases Consumer Expenditures Increase In Personal Income Increases Consumer Expenditure Personal Income 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 43101 26876 26483 26217 26473 26799 27534 28118 29352 30808 31120 31462 31185 30959 31029 30935 31354 32205 32324 30997 30661 30211 29750 29572 29883 30532 32051 32542 32741 33706 Consumer expenditures 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 43101 4.0750000000000002 3.5750000000000002 3.05 2.7 2.2250000000000001 2.1749999999999998 1.9 1.7749999999999999 1.3 1.35 1.75 1.7749999999999999 1.675 1.45 1.95 2.15 2.2999999999999998 2.2000000000000002 2.0249999999999999 1.1499999999999999 1.35 1.575 1.875 1.5 1.6 1.25 1.6 1.65 1.925 Income, Wealth, And Poverty As the inflation rate increases poverty also increase Increase In Inflation Increases Poverty Higher Inflation Increases The Poverty Inflation rate 32509 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 4.1500000000000004 4.0750000000000002 3.5750000000000002 3.05 2.7 2.2250000000000001 2.1749999999999998 1.9 1.7749999999999999 1.3 1.35 1.75 1.7749999999999999 1.675 1.45 1.95 2.15 2.2999999999999998 2.2000000000000002 2.0249999999999999 1.1499999999999999 1.35 1.575 1.875 1.5 1.6 1.25 1.6 1.65 Poverty 32509 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 31528020 33875346 35917654 38291114 39264811 37191809 36424609 36529140 35573858 34475762 32791272 31581086 32906511 34569951 35861170 37039804 38231474 38757253 38052247 39108422 42868163 46215956 48452035 48760123 48810868 48208387 46153077 44268996 42583651 Business Statistics As we can see in the graph the increase in sales of company does not necessary increases profits. Some company’s profits increases with sales and some company’s decreases. Increase In Sales Decreases Profits? Is The Profits Of Company Is Affected By Sales? 179.5 132.9 150.30000000000001 137.5 111.9 261.7 151.80000000000001 126.7 382.6 101.5 279.2 170.8 221.5 100 272.10000000000002 118.2 137 278.2 158.69999999999999 130.9 64.3 322.8 118.8 299.10000000000002 184.2 247.8 111.8 232.9 514.4 89.5 45.2 32.700000000000003 38.799999999999997 30.9 28.5 59.4 16.3 27.5 23.3 23.1 20.8 19.399999999999999 39.9 17.899999999999999 17.2 33.5 30.7 14 14.8 15.5 13.7 ...

Data Analysis Project 3
Presented By: Yiwen Li
National Economy
Above graph shows the personal income relation with consumer
expenditure.
Consumer expenditure is in % as personal income increases
consumer expenditure also increases.
Increase In Personal Income Increases Consumer Expenditures
Increase In Personal Income Increases Consumer Expenditure
Personal Income 32874 33239 33604 33970
34335 34700 35065 35431 35796 36161
36526 36892 37257 37622 37987 38353
38718 39083 39448 39814 40179 40544
40909 41275 41640 42005 42370 42736
43101 26876 26483 26217 26473 26799
27534 28118 29352 30808 31120 31462
31185 30959 31029 30935 31354 32205
32324 30997 30661 30211 29750 29572
29883 30532 32051 32542 32741 33706
Consumer expenditures 32874 33239 33604
33970 34335 34700 35065 35431 35796
36161 36526 36892 37257 37622 37987
38353 38718 39083 39448 39814 40179
40544 40909 41275 41640 42005 42370
42736 43101 4.0750000000000002
3.5750000000000002 3.05 2.7 2.2250000000000001
2.1749999999999998 1.9 1.7749999999999999
1.3 1.35 1.75 1.7749999999999999 1.675 1.45
1.95 2.15 2.2999999999999998 2.2000000000000002
2.0249999999999999 1.1499999999999999 1.35
1.575 1.875 1.5 1.6 1.25 1.6 1.65 1.925
Income, Wealth,
And Poverty
As the inflation rate increases poverty also increase
Increase In Inflation Increases Poverty
Higher Inflation Increases The Poverty
Inflation rate 32509 32874 33239 33604 33970
34335 34700 35065 35431 35796 36161
36526 36892 37257 37622 37987 38353
38718 39083 39448 39814 40179 40544
40909 41275 41640 42005 42370 42736
4.1500000000000004 4.0750000000000002
3.5750000000000002 3.05 2.7 2.2250000000000001
2.1749999999999998 1.9 1.7749999999999999
1.3 1.35 1.75 1.7749999999999999 1.675 1.45
1.95 2.15 2.2999999999999998 2.2000000000000002
2.0249999999999999 1.1499999999999999 1.35
1.575 1.875 1.5 1.6 1.25 1.6 1.65 Poverty
32509 32874 33239 33604 33970 34335
34700 35065 35431 35796 36161 36526
36892 37257 37622 37987 38353 38718
39083 39448 39814 40179 40544 40909
41275 41640 42005 42370 42736
31528020 33875346 35917654 38291114 39264811
37191809 36424609 36529140 35573858 34475762
32791272 31581086 32906511 34569951 35861170
37039804 38231474 38757253 38052247 39108422
42868163 46215956 48452035 48760123 48810868
48208387 46153077 44268996 42583651
Business Statistics
As we can see in the graph the increase in sales of company
does not necessary increases profits.
Some company’s profits increases with sales and some
company’s decreases.
Increase In Sales Decreases Profits?
Is The Profits Of Company Is Affected By Sales?
179.5 132.9 150.30000000000001 137.5 111.9
261.7 151.80000000000001 126.7 382.6
101.5 279.2 170.8 221.5 100
272.10000000000002 118.2 137 278.2
158.69999999999999 130.9 64.3 322.8 118.8
299.10000000000002 184.2 247.8 111.8
232.9 514.4 89.5 45.2 32.700000000000003
38.799999999999997 30.9 28.5 59.4 16.3 27.5 23.3
23.1 20.8 19.399999999999999 39.9
17.899999999999999 17.2 33.5 30.7 14 14.8 15.5
13.7 8 8.8000000000000007 9.3000000000000007
11.4 4 17.899999999999999 10.1 6.7
9.1999999999999993
Sales (x)
Profit (y)
Labor Statistics
This graph shows the relation between wages and compensation.
And we can see as the wage is high compensation would be
high.
High Wages And Salaries High Compensation
High Wages And Salaries Compensation Would Be High
Wages and Salaries 88.8 91.65 94.25 96.75 99.15
102.05 105.5 108.625 110.35 112.125 113.95
116.02500000000001 118.22499999999999
120.625 123.325 126.25 129.5 133.4
Compensation 6039.1360000000004
6135.5690000000004 6354.0540000000001
6720.058 7066.6049999999996 7479.8950000000004
7878.8620000000001 8056.9780000000001
7758.509 7924.9359999999997 8225.9310000000005
8566.7250000000004 8834.2219999999998
9249.0969999999998 9698.1550000000007
9960.3240000000005 10411.61 10928.451999999999
Government
In this graph we have shown the relation of Monetary base with
Government expenditure and tax receipts.
As the monetary base increases the government expenditure and
tax receipts also increases.
Increase In Monetary Base Increases Government Expenditure
And Tax Receipts
Increase In Monetory Base Increase Government Expenditure
And Tax Reciepts
Government expenditures 188.59347826086957
201.52280769230768 220.64444444444445
241.70265384615385 259.33184615384613
271.31900000000002 290.68584615384617
318.31619230769229 347.92415384615384
386.34903846153844 423.92411538461539
447.81023076923077 466.0031923076923
494.0465185185185 525.78438461538462
575.55984615384614 607.17700000000002
641.48850000000004 697.55957692307697
741.44226923076928 777.28146153846149
806.99311538461541 835.67753846153846
851.59161538461535 1006.4374814814814
1800.0028846153846 2033.9342307692307
2540.3868846153846 2665.5889999999999
3264.3584230769229 3948.9493461538464
4008.0866538461537 3794.8531153846152
3826.0761538461538 3675.6930384615384
3315.9072500000002 1368.66875
1496.8432499999999 1597.895 1681.1692499999999
1764.4590000000001 1896.99325
2055.4250000000002 2166.643 2339.2362499999999
2412.7517499999999 2485.7809999999999
2601.7807499999999 2696.96425 2772.35275
2855.5895 2995.8285000000001 3142.05125
3362.4059999999999 3585.2062500000002
3816.09575 4019.4115000000002
4303.4972500000003 4519.9692500000001
4833.6350000000002 5260.7197500000002
5634.2394999999997 5833.4447499999997
5872.1222500000003 5842.4390000000003
5854.1237499999997 6002.2122499999996
6165.90175 6377.5797499999999
6597.4307500000004 6930.3842500000001 0
Tax recipts
188.59347826086957 201.52280769230768
220.64444444444445 241.70265384615385
259.33184615384613 271.31900000000002
290.68584615384617 318.31619230769229
347.92415384615384 386.34903846153844
423.92411538461539 447.81023076923077
466.0031923076923 494.0465185185185
525.78438461538462 575.55984615384614
607.17700000000002 641.48850000000004
697.55957692307697 741.44226923076928
777.28146153846149 806.99311538461541
835.67753846153846 851.59161538461535
1006.4374814814814 1800.0028846153846
2033.9342307692307 2540.3868846153846
2665.5889999999999 3264.3584230769229
3948.9493461538464 4008.0866538461537
3794.8531153846152 3826.0761538461538
3675.6930384615384 3315.9072500000002
409.68099999999998 442.91300000000001
462.03399999999999 526.41575
549.80799999999999 601.14400000000001
620.56299999999999 617.11575000000005
645.42425000000003 699.26774999999998
763.46325000000002 825.69725000000005
916.95775000000003 1015.09075 1095.258
1174.5372500000001 1288.53125 1226.82275
1053.18425 1053.864 1140.5965000000001
1367.8232499999999 1534.7755
1607.6567500000001 1489.5160000000001
1123.66525 1273.5977499999999
1478.4034999999999 1572.9502500000001
1744.8855000000001 1900.05475 2023.05
2019.39 2019.16275 1956.0809999999999 0
Monetory Base
Thank You !
National EconomyIncrease in Personal income increases
consumer expenditures?Observation_datePersonal
IncomeConsumer expenditures1990-01-01268764.11991-01-
01264833.61992-01-01262173.11993-01-01264732.71994-01-
01267992.21995-01-01275342.21996-01-01281181.91997-01-
01293521.81998-01-01308081.31999-01-01311201.42000-01-
01314621.82001-01-01311851.82002-01-01309591.72003-01-
01310291.52004-01-01309352.02005-01-01313542.22006-01-
01322052.32007-01-01323242.22008-01-01309972.02009-01-
01306611.22010-01-01302111.42011-01-01297501.62012-01-
01295721.92013-01-01298831.52014-01-01305321.62015-01-
01320511.32016-01-01325421.62017-01-01327411.72018-01-
01337061.9Statistical MetricsMean
301342Median308082Sample
Variance4392205.189655170.4524368842Standard
Deviation2095.75885770650.6726342871Coefficient of
Variation6.95%34.30%Max337064Min262171Range74893Perce
ntile 32367.62.77Quartile293521.575Skewness-
0.59592289321.680161164
Increase in personal income increases consumer expenditure
Personal Income 32874 33239 33604 33970
34335 34700 35065 35431 35796 36161
36526 36892 37257 37622 37987 38353
38718 39083 39448 39814 40179 40544
40909 41275 41640 42005 42370 42736
43101 26876 26483 26217 26473 26799
27534 28118 29352 30808 31120 31462
31185 30959 31029 30935 31354 32205
32324 30997 30661 30211 29750 29572
29883 30532 32051 32542 32741 33706
Consumer expenditures 32874 33239 33604
33970 34335 34700 35065 35431 35796
36161 36526 36892 37257 37622 37987
38353 38718 39083 39448 39814 40179
40544 40909 41275 41640 42005 42370
42736 43101 4.0750000000000002
3.5750000000000002 3.05 2.7 2.2250000000000001
2.1749999999999998 1.9 1.7749999999999999
1.3 1.35 1.75 1.7749999999999999 1.675 1.45
1.95 2.15 2.2999999999999998 2.2000000000000002
2.0249 999999999999 1.1499999999999999 1.35
1.575 1.875 1.5 1.6 1.25 1.6 1.65 1.925
Wealth, Income, and PovertyHigher Inflation increases the
poverty?Observation_dateInflation ratePoverty1989-01-
014.2315280201990-01-014.1338753461991-01-
013.6359176541992-01-013.1382911141993-01-
012.7392648111994-01-012.2371918091995-01-
012.2364246091996-01-011.9365291401997-01-
011.8355738581998-01-011.3344757621999-01-
011.4327912722000-01-011.8315810862001-01-
011.8329065112002-01-011.7345699512003-01-
011.5358611702004-01-012.0370398042005-01-
012.2382314742006-01-012.3387572532007-01-
012.2380522472008-01-012.0391084222009-01-
011.2428681632010-01-011.4462159562011-01-
011.6484520352012-01-011.9487601232013-01-
011.5488108682014-01-011.6482083872015-01-
011.3461530772016-01-011.6442689962017-01-
011.742583651Statistical MetricsMean
2.037931034539113536.862069Median1.77538052247Sample
Variance0.617393780829644929955060.6Standard
Deviation0.78574409375444715.78276227Coefficient of
Variation39%14%Max4.1548810868Min1.1531528020Range317
282848Percentile
3.15548257116.6Quitiles1.57535573858Skewness1.5675196079
0.5835847881
Higher Inflation increases the poverty
Inflation rate 32509 32874 33239 33604 33970
34335 34700 35065 35431 35796 36161
36526 36892 37257 37622 37987 38353
38718 39083 39448 39814 40179 40544
40909 41275 41640 42005 42370 42736
4.1500000000000004 4.0750000000000002
3.5750000000000002 3.05 2.7 2.2250000000000001
2.1749999999999998 1.9 1.7749999999999999
1.3 1.35 1.75 1.7749999999999999 1.675 1.45
1.95 2.15 2.2999999999999998 2.2000000000000002
2.0249999999999999 1.1499999999999999 1.35
1.575 1.875 1.5 1.6 1.25 1.6 1.65 Poverty
32509 32874 33239 33604 33970 34335
34700 35065 35431 35796 36161 36526
36892 37257 37622 37987 38353 38718
39083 39448 39814 40179 40544 40909
41275 41640 42005 42370 42736
31528020 33875346 35917654 38291114 39264811
37191809 36424609 36529140 35573858 34475762
32791272 31581086 32906511 34569951 35861170
37039804 38231474 38757253 38052247 39108422
42868163 46215956 48452035 48760123 48810868
48208387 46153077 44268996 42583651
Business Statistics Increase in sales increases profits?Company
NameSales ($) (Billions)Profits ($) (Billions)ICBC179.545.2JP
Morgan Chase 132.932.7China construction
bank150.338.8Agriculture Bank of China137.530.9Bank of
America111.928.5Apple 261.759.4Ping An Insurance Group
151.816.3Bank of China 126.727.5Royal Dutch
Shell382.623.3Wells Fargo101.523.1Exxon Mobil
279.220.8AT&T170.819.4Samsung
Electronics221.539.9citigroup10017.9toyota
motor272.117.2microsoft118.233.5alphabet13730.7volkswagen
group278.214chevron158.714.8verizon
communications130.915.5HSBC holdings64.313.7petro
china322.88allianz118.88.8BP299.19.3total184.211.4berkshire
hathaway247.84china
mobile111.817.9amazon232.910.1walmart514.46.7santander89.
59.2Statistical MetricsMean
192.953333333321.6166666667Median155.2517.9Sample
Variance10018.0418850575167.0359195402Standard
Deviation100.090168773212.9242376773Coefficient of
Variation52%60%Max514.459.4Min64.34Range450.155.4Perce
ntile
301.4738.91Quitiles120.77511.975Skewness1.39143728681.056
6186151Single RegressionSales ($) (Billions)Profits ($)
(Billions)Sales ($) (Billions)1Profits ($) (Billions)-
0.18038176081Multiple Regression
Is the profits of company is affected by Sales?
179.5 132.9 150.30000000000001 137.5 111.9
261.7 151.80000000000001 126.7 382.6
101.5 279.2 170.8 221.5 100
272.10000000000002 118.2 137 278.2
158.69999999999999 130.9 64.3 322.8 118.8
299.10000000000002 184.2 247.8 111.8
232.9 514.4 89.5 45.2 32.700000000000003
38.799999999999997 30.9 28.5 59.4 16.3 27.5 23.3
23.1 20.8 19.399999999999999 39.9
17.899999999999999 17.2 33.5 30.7 14 14.8 15.5
13.7 8 8.8000000000000007 9.3000000000000007
11.4 4 17.899999999999999 10.1 6.7
9.1999999999999993
Sales (x)
Profit (y)
Labor StatisticsHigh wages and salaries high
compensation?Observation DateWages and
SalariesCompensation2001-01-0188.86039.1362002-01-
0191.76135.5692003-01-0194.36354.0542004-01-
0196.86720.0582005-01-0199.27066.6052006-01-
01102.17479.8952007-01-01105.57878.8622008-01-
01108.68056.9782009-01-01110.47758.5092010-01-
01112.17924.9362011-01-01114.08225.9312012-01-
01116.08566.7252013-01-01118.28834.2222014-01-
01120.69249.0972015-01-01123.39698.1552016-01-
01126.39960.3242017-01-01129.510411.6102018-01-
01133.410928.452Statistical MetricsMean
110.68182.7Median111.27991.0Sample
Variance177.24589869282119868.16933351Standard
Deviation13.3133729271455.9767063156Coefficient of
Variation12%18%Max133.410928.5Min88.86039.1Range44.648
89.3Percentile
127.22510095.7098Quitiles99.8757169.9275Skewness-
0.00518404290.276182045
High wages and salaries compensation would be high
Wages and Salaries 88.8 91.65 94.25 96.75 99.15
102.05 105.5 108.625 110.35 112.125 113.95
116.02500000000001 118.22499999999999
120.625 123.325 126.25 129.5 133.4
Compensation 6039.136 0000000004
6135.5690000000004 6354.0540000000001
6720.058 7066.6049999999996 7479.8950000000004
7878.8620000000001 8056.9780000000001
7758.509 7924.9359999999997 8225.9310000000005
8566.7250000000004 8834.2219999999998
9249.0969999999998 9698.1550000000007
9960.3240000000005 10411.61 10928.451999999999
GovernmentIncrease in Monetory base increases government
expenditures and tax reciepts?Observation_dateMonetory
baseGovernment expendituresTax recipts1984-01-
01188.5931368.669409.6811985-01-
01201.5231496.843442.913SUMMARY OUTPUT1986-01-
01220.6441597.895462.0341987-01-
01241.7031681.169526.416Regression Statistics1988-01-
01259.3321764.459549.808Multiple R0.7219177861989-01-
01271.3191896.993601.144R Square0.52116528981990-01-
01290.6862055.425620.563Adjusted R
Square0.49214500431991-01-
01318.3162166.643617.116Standard Error947.4426158431992-
01-01347.9242339.236645.424Observations361993-01-
01386.3492412.752699.2681994-01-
01423.9242485.781763.463ANOVA1995-01-
01447.8102601.781825.697dfSSMSFSignificance F1996-01-
01466.0032696.964916.958Regression232241083.59348916120
541.796744517.958654830.00000528521997-01-
01494.0472772.3531015.091Residual3329622367.84041198976
47.5103155121998-01-
01525.7842855.5901095.258Total3561863451.43390091999-01-
01575.5602995.8291174.5372000-01-
01607.1773142.0511288.531CoefficientsStandard Errort StatP-
valueLower 95%Upper 95%Lower 95.0%Upper 95.0%2001-01-
01641.4893362.4061226.823Intercept-
622.7136666805371.7377431454-1.67514243080.1033585102-
1379.0197917491133.5924583882-
1379.0197917491133.59245838822002-01-
01697.5603585.2061053.184Government
expenditures0.48200048630.26381655821.8270289390.0767519
364-0.0547383371.0187393097-
0.0547383371.01873930972003-01-
01741.4423816.0961053.864Tax
recipts0.14270963380.9128629180.15633194310.8767238587-
1.71452393741.9999432049-1.71452393741.99994320492004-
01-01777.2814019.4121140.5972005-01-
01806.9934303.4971367.8232006-01-
01835.6784519.9691534.7762007-01-
01851.5924833.6351607.657RESIDUAL OUTPUT2008-01-
011006.4375260.7201489.5162009-01-
011800.0035634.2401123.665ObservationPredicted Monetory
baseResiduals2010-01-
012033.9345833.4451273.598195.450761945893.142716315120
11-01-
012540.3875872.1221478.4042161.97345983339.549347859320
12-01-
012665.5895842.4391572.9503213.40920338697.235241057520
13-01-013264.3585854.1241744.8864262.7353283517-
21.03267450552014-01-
013948.9496002.2121900.0555306.2193277903-
46.88748163642015-01-
014008.0876165.9022023.0506377.4270425078-
106.10804250782016-01-
013794.8536377.5802019.3907456.5625014393-
165.87665528542017-01-
013826.0766597.4312019.1638509.677675745-
191.36148343732018-01-
013675.6936930.3841956.0819596.9076018534-
248.98344800732019-01-013315.9070010640.0260947739-
253.677056312311684.3875450866-
260.46342970212749.1808723515-
301.370641582213808.0831181771-
342.079925869414858.4249363336-
364.37841781515909.985729204-
384.201344588616988.8949081427-
413.3350619889171075.6423867507-
468.4653867507181173.0470859843-
531.5585859843191255.6570280987-
558.0974511756201367.0428862653-
625.6006170345211477.4187399592-
700.1372784208221646.7756559007-
839.7825405161231774.9409596373-
939.2634211758241936.5288601851-
1084.9372448005252125.5240942311-
1119.0866127496262253.3503688432-
453.3474842278272370.7642083926-
336.8299776234282418.6345357811121.7523488343292417.81
99269118247.7690730882302447.9887986553816.36962442163
12541.51167451891407.437671635322637.96270021281370.12
39536334332739.46928190271055.3838334819342845.4051400
628980.6710137833352996.8865155542678.806522907436-
622.71366668053938.6209166805
Increase in Monetory base increase government expenditure and
Tax reciepts
Government expenditures 188.59347826086957
201.52280769230768 220.64444444444445
241.70265384615385 259.33184615384613
271.31900000000002 290.68584615384617
318.31619230769229 347.92415384615384
386.34903846153844 423.92411538461539
447.81023076923077 466.0031923076923
494.0465185185185 525.78438461538462
575.55984615384614 607.17700000000002
641.48850000000004 697.55957692307697
741.44226923076928 777.281461538461 49
806.99311538461541 835.67753846153846
851.59161538461535 1006.4374814814814
1800.0028846153846 2033.9342307692307
2540.3868846153846 2665.5889999999999
3264.3584230769229 3948.9493461538464
4008.0866538461537 3794.8531153846152
3826.0761538461538 3675.6930384615384
3315.9072500000002 1368.66875
1496.8432499999999 1597.895 1681.1692499999999
1764.4590000000001 1896.99325
2055.4250000000002 2166.643 2339.2362499999999
2412.7517499999999 2485.7809999999999
2601.7807499999999 2696.96425 2772.35275
2855.5895 2995.8285000000001 3142.05125
3362.4059999999999 3585.2062500000002
3816.09575 4019.4115000000002
4303.4972500000003 4519.9692500000001
4833.6350000 000002 5260.7197500000002
5634.2394999999997 5833.4447499999997
5872.1222500000003 5842.4390000000003
5854.1237499999997 6002.2122499999996
6165.90175 6377.5797499999999
6597.4307500000004 6930.3842500000001 0
Tax recipts
188.59347826086957 201.52280769230768
220.64444444444445 241.70265384615385
259.33184615384613 271.31900000000002
290.68584615384617 318.31619230769229
347.92415384615384 386.34903846153844
423.92411538461539 447.81023076923077
466.0031923076923 494.0465185185185
525.78438461538462 575.55984615384614
607.17700000000002 641.48850000000004
697.55957692307697 741.44226923076928
777.28146153846149 806.99311538461541
835.67753846153846 851.59161538461535
1006.4374814814814 1800.0028846153846
2033.9342307692307 2540.3868846153846
2665.5889999999999 3264.3584230769229
3948.9493461538464 4008.0866538461537
3794.8531153846152 3826.0761538461538
3675.6930384615384 3315.9072500000002
409.68099999999998 442.91300000000001
462.03399999999999 526.41575
549.80799999999999 601.14400000000001
620.56299999999999 617.11575000000005
645.42425000000003 699.26774999999998
763.46325000000002 825.69725000000005
916.95775000000003 1015.09075 1095.258
1174.5372500000001 1288.53125 1226.82275
1053.18425 1053.864 1140.5965000000001
1367.8232499999999 1534.7755
1607.6567500000001 1489.5160000000001
1123.66525 1273.5977499999999
1478.4034999999999 1572.9502500000001
1744.8855000000001 1900.05475 2023.05
2019.39 2019.16275 1956.0809999999999 0
Monetory Base

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  • 1. Data Analysis Project 3 Presented By: Yiwen Li National Economy Above graph shows the personal income relation with consumer expenditure. Consumer expenditure is in % as personal income increases consumer expenditure also increases. Increase In Personal Income Increases Consumer Expenditures Increase In Personal Income Increases Consumer Expenditure Personal Income 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 43101 26876 26483 26217 26473 26799 27534 28118 29352 30808 31120 31462 31185 30959 31029 30935 31354 32205 32324 30997 30661 30211 29750 29572 29883 30532 32051 32542 32741 33706 Consumer expenditures 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 43101 4.0750000000000002
  • 2. 3.5750000000000002 3.05 2.7 2.2250000000000001 2.1749999999999998 1.9 1.7749999999999999 1.3 1.35 1.75 1.7749999999999999 1.675 1.45 1.95 2.15 2.2999999999999998 2.2000000000000002 2.0249999999999999 1.1499999999999999 1.35 1.575 1.875 1.5 1.6 1.25 1.6 1.65 1.925 Income, Wealth, And Poverty As the inflation rate increases poverty also increase Increase In Inflation Increases Poverty Higher Inflation Increases The Poverty Inflation rate 32509 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 4.1500000000000004 4.0750000000000002 3.5750000000000002 3.05 2.7 2.2250000000000001 2.1749999999999998 1.9 1.7749999999999999 1.3 1.35 1.75 1.7749999999999999 1.675 1.45 1.95 2.15 2.2999999999999998 2.2000000000000002 2.0249999999999999 1.1499999999999999 1.35 1.575 1.875 1.5 1.6 1.25 1.6 1.65 Poverty 32509 32874 33239 33604 33970 34335
  • 3. 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 31528020 33875346 35917654 38291114 39264811 37191809 36424609 36529140 35573858 34475762 32791272 31581086 32906511 34569951 35861170 37039804 38231474 38757253 38052247 39108422 42868163 46215956 48452035 48760123 48810868 48208387 46153077 44268996 42583651 Business Statistics As we can see in the graph the increase in sales of company does not necessary increases profits. Some company’s profits increases with sales and some company’s decreases. Increase In Sales Decreases Profits? Is The Profits Of Company Is Affected By Sales? 179.5 132.9 150.30000000000001 137.5 111.9 261.7 151.80000000000001 126.7 382.6 101.5 279.2 170.8 221.5 100 272.10000000000002 118.2 137 278.2 158.69999999999999 130.9 64.3 322.8 118.8 299.10000000000002 184.2 247.8 111.8
  • 4. 232.9 514.4 89.5 45.2 32.700000000000003 38.799999999999997 30.9 28.5 59.4 16.3 27.5 23.3 23.1 20.8 19.399999999999999 39.9 17.899999999999999 17.2 33.5 30.7 14 14.8 15.5 13.7 8 8.8000000000000007 9.3000000000000007 11.4 4 17.899999999999999 10.1 6.7 9.1999999999999993 Sales (x) Profit (y) Labor Statistics This graph shows the relation between wages and compensation. And we can see as the wage is high compensation would be high. High Wages And Salaries High Compensation High Wages And Salaries Compensation Would Be High Wages and Salaries 88.8 91.65 94.25 96.75 99.15 102.05 105.5 108.625 110.35 112.125 113.95 116.02500000000001 118.22499999999999 120.625 123.325 126.25 129.5 133.4 Compensation 6039.1360000000004 6135.5690000000004 6354.0540000000001 6720.058 7066.6049999999996 7479.8950000000004 7878.8620000000001 8056.9780000000001 7758.509 7924.9359999999997 8225.9310000000005
  • 5. 8566.7250000000004 8834.2219999999998 9249.0969999999998 9698.1550000000007 9960.3240000000005 10411.61 10928.451999999999 Government In this graph we have shown the relation of Monetary base with Government expenditure and tax receipts. As the monetary base increases the government expenditure and tax receipts also increases. Increase In Monetary Base Increases Government Expenditure And Tax Receipts Increase In Monetory Base Increase Government Expenditure And Tax Reciepts Government expenditures 188.59347826086957 201.52280769230768 220.64444444444445 241.70265384615385 259.33184615384613 271.31900000000002 290.68584615384617 318.31619230769229 347.92415384615384 386.34903846153844 423.92411538461539 447.81023076923077 466.0031923076923 494.0465185185185 525.78438461538462 575.55984615384614 607.17700000000002 641.48850000000004 697.55957692307697 741.44226923076928 777.28146153846149 806.99311538461541 835.67753846153846
  • 6. 851.59161538461535 1006.4374814814814 1800.0028846153846 2033.9342307692307 2540.3868846153846 2665.5889999999999 3264.3584230769229 3948.9493461538464 4008.0866538461537 3794.8531153846152 3826.0761538461538 3675.6930384615384 3315.9072500000002 1368.66875 1496.8432499999999 1597.895 1681.1692499999999 1764.4590000000001 1896.99325 2055.4250000000002 2166.643 2339.2362499999999 2412.7517499999999 2485.7809999999999 2601.7807499999999 2696.96425 2772.35275 2855.5895 2995.8285000000001 3142.05125 3362.4059999999999 3585.2062500000002 3816.09575 4019.4115000000002 4303.4972500000003 4519.9692500000001 4833.6350000000002 5260.7197500000002 5634.2394999999997 5833.4447499999997 5872.1222500000003 5842.4390000000003 5854.1237499999997 6002.2122499999996 6165.90175 6377.5797499999999 6597.4307500000004 6930.3842500000001 0 Tax recipts 188.59347826086957 201.52280769230768 220.64444444444445 241.70265384615385 259.33184615384613 271.31900000000002 290.68584615384617 318.31619230769229 347.92415384615384 386.34903846153844 423.92411538461539 447.81023076923077 466.0031923076923 494.0465185185185 525.78438461538462 575.55984615384614 607.17700000000002 641.48850000000004 697.55957692307697 741.44226923076928 777.28146153846149 806.99311538461541 835.67753846153846 851.59161538461535
  • 7. 1006.4374814814814 1800.0028846153846 2033.9342307692307 2540.3868846153846 2665.5889999999999 3264.3584230769229 3948.9493461538464 4008.0866538461537 3794.8531153846152 3826.0761538461538 3675.6930384615384 3315.9072500000002 409.68099999999998 442.91300000000001 462.03399999999999 526.41575 549.80799999999999 601.14400000000001 620.56299999999999 617.11575000000005 645.42425000000003 699.26774999999998 763.46325000000002 825.69725000000005 916.95775000000003 1015.09075 1095.258 1174.5372500000001 1288.53125 1226.82275 1053.18425 1053.864 1140.5965000000001 1367.8232499999999 1534.7755 1607.6567500000001 1489.5160000000001 1123.66525 1273.5977499999999 1478.4034999999999 1572.9502500000001 1744.8855000000001 1900.05475 2023.05 2019.39 2019.16275 1956.0809999999999 0 Monetory Base Thank You ! National EconomyIncrease in Personal income increases consumer expenditures?Observation_datePersonal IncomeConsumer expenditures1990-01-01268764.11991-01- 01264833.61992-01-01262173.11993-01-01264732.71994-01- 01267992.21995-01-01275342.21996-01-01281181.91997-01-
  • 8. 01293521.81998-01-01308081.31999-01-01311201.42000-01- 01314621.82001-01-01311851.82002-01-01309591.72003-01- 01310291.52004-01-01309352.02005-01-01313542.22006-01- 01322052.32007-01-01323242.22008-01-01309972.02009-01- 01306611.22010-01-01302111.42011-01-01297501.62012-01- 01295721.92013-01-01298831.52014-01-01305321.62015-01- 01320511.32016-01-01325421.62017-01-01327411.72018-01- 01337061.9Statistical MetricsMean 301342Median308082Sample Variance4392205.189655170.4524368842Standard Deviation2095.75885770650.6726342871Coefficient of Variation6.95%34.30%Max337064Min262171Range74893Perce ntile 32367.62.77Quartile293521.575Skewness- 0.59592289321.680161164 Increase in personal income increases consumer expenditure Personal Income 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 43101 26876 26483 26217 26473 26799 27534 28118 29352 30808 31120 31462 31185 30959 31029 30935 31354 32205 32324 30997 30661 30211 29750 29572 29883 30532 32051 32542 32741 33706 Consumer expenditures 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 43101 4.0750000000000002 3.5750000000000002 3.05 2.7 2.2250000000000001 2.1749999999999998 1.9 1.7749999999999999 1.3 1.35 1.75 1.7749999999999999 1.675 1.45 1.95 2.15 2.2999999999999998 2.2000000000000002
  • 9. 2.0249 999999999999 1.1499999999999999 1.35 1.575 1.875 1.5 1.6 1.25 1.6 1.65 1.925 Wealth, Income, and PovertyHigher Inflation increases the poverty?Observation_dateInflation ratePoverty1989-01- 014.2315280201990-01-014.1338753461991-01- 013.6359176541992-01-013.1382911141993-01- 012.7392648111994-01-012.2371918091995-01- 012.2364246091996-01-011.9365291401997-01- 011.8355738581998-01-011.3344757621999-01- 011.4327912722000-01-011.8315810862001-01- 011.8329065112002-01-011.7345699512003-01- 011.5358611702004-01-012.0370398042005-01- 012.2382314742006-01-012.3387572532007-01- 012.2380522472008-01-012.0391084222009-01- 011.2428681632010-01-011.4462159562011-01- 011.6484520352012-01-011.9487601232013-01- 011.5488108682014-01-011.6482083872015-01- 011.3461530772016-01-011.6442689962017-01- 011.742583651Statistical MetricsMean 2.037931034539113536.862069Median1.77538052247Sample Variance0.617393780829644929955060.6Standard Deviation0.78574409375444715.78276227Coefficient of Variation39%14%Max4.1548810868Min1.1531528020Range317 282848Percentile 3.15548257116.6Quitiles1.57535573858Skewness1.5675196079 0.5835847881 Higher Inflation increases the poverty Inflation rate 32509 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544
  • 10. 40909 41275 41640 42005 42370 42736 4.1500000000000004 4.0750000000000002 3.5750000000000002 3.05 2.7 2.2250000000000001 2.1749999999999998 1.9 1.7749999999999999 1.3 1.35 1.75 1.7749999999999999 1.675 1.45 1.95 2.15 2.2999999999999998 2.2000000000000002 2.0249999999999999 1.1499999999999999 1.35 1.575 1.875 1.5 1.6 1.25 1.6 1.65 Poverty 32509 32874 33239 33604 33970 34335 34700 35065 35431 35796 36161 36526 36892 37257 37622 37987 38353 38718 39083 39448 39814 40179 40544 40909 41275 41640 42005 42370 42736 31528020 33875346 35917654 38291114 39264811 37191809 36424609 36529140 35573858 34475762 32791272 31581086 32906511 34569951 35861170 37039804 38231474 38757253 38052247 39108422 42868163 46215956 48452035 48760123 48810868 48208387 46153077 44268996 42583651 Business Statistics Increase in sales increases profits?Company NameSales ($) (Billions)Profits ($) (Billions)ICBC179.545.2JP Morgan Chase 132.932.7China construction bank150.338.8Agriculture Bank of China137.530.9Bank of America111.928.5Apple 261.759.4Ping An Insurance Group 151.816.3Bank of China 126.727.5Royal Dutch Shell382.623.3Wells Fargo101.523.1Exxon Mobil 279.220.8AT&T170.819.4Samsung Electronics221.539.9citigroup10017.9toyota motor272.117.2microsoft118.233.5alphabet13730.7volkswagen group278.214chevron158.714.8verizon communications130.915.5HSBC holdings64.313.7petro china322.88allianz118.88.8BP299.19.3total184.211.4berkshire
  • 11. hathaway247.84china mobile111.817.9amazon232.910.1walmart514.46.7santander89. 59.2Statistical MetricsMean 192.953333333321.6166666667Median155.2517.9Sample Variance10018.0418850575167.0359195402Standard Deviation100.090168773212.9242376773Coefficient of Variation52%60%Max514.459.4Min64.34Range450.155.4Perce ntile 301.4738.91Quitiles120.77511.975Skewness1.39143728681.056 6186151Single RegressionSales ($) (Billions)Profits ($) (Billions)Sales ($) (Billions)1Profits ($) (Billions)- 0.18038176081Multiple Regression Is the profits of company is affected by Sales? 179.5 132.9 150.30000000000001 137.5 111.9 261.7 151.80000000000001 126.7 382.6 101.5 279.2 170.8 221.5 100 272.10000000000002 118.2 137 278.2 158.69999999999999 130.9 64.3 322.8 118.8 299.10000000000002 184.2 247.8 111.8 232.9 514.4 89.5 45.2 32.700000000000003 38.799999999999997 30.9 28.5 59.4 16.3 27.5 23.3 23.1 20.8 19.399999999999999 39.9 17.899999999999999 17.2 33.5 30.7 14 14.8 15.5 13.7 8 8.8000000000000007 9.3000000000000007 11.4 4 17.899999999999999 10.1 6.7 9.1999999999999993 Sales (x) Profit (y) Labor StatisticsHigh wages and salaries high
  • 12. compensation?Observation DateWages and SalariesCompensation2001-01-0188.86039.1362002-01- 0191.76135.5692003-01-0194.36354.0542004-01- 0196.86720.0582005-01-0199.27066.6052006-01- 01102.17479.8952007-01-01105.57878.8622008-01- 01108.68056.9782009-01-01110.47758.5092010-01- 01112.17924.9362011-01-01114.08225.9312012-01- 01116.08566.7252013-01-01118.28834.2222014-01- 01120.69249.0972015-01-01123.39698.1552016-01- 01126.39960.3242017-01-01129.510411.6102018-01- 01133.410928.452Statistical MetricsMean 110.68182.7Median111.27991.0Sample Variance177.24589869282119868.16933351Standard Deviation13.3133729271455.9767063156Coefficient of Variation12%18%Max133.410928.5Min88.86039.1Range44.648 89.3Percentile 127.22510095.7098Quitiles99.8757169.9275Skewness- 0.00518404290.276182045 High wages and salaries compensation would be high Wages and Salaries 88.8 91.65 94.25 96.75 99.15 102.05 105.5 108.625 110.35 112.125 113.95 116.02500000000001 118.22499999999999 120.625 123.325 126.25 129.5 133.4 Compensation 6039.136 0000000004 6135.5690000000004 6354.0540000000001 6720.058 7066.6049999999996 7479.8950000000004 7878.8620000000001 8056.9780000000001 7758.509 7924.9359999999997 8225.9310000000005 8566.7250000000004 8834.2219999999998 9249.0969999999998 9698.1550000000007 9960.3240000000005 10411.61 10928.451999999999
  • 13. GovernmentIncrease in Monetory base increases government expenditures and tax reciepts?Observation_dateMonetory baseGovernment expendituresTax recipts1984-01- 01188.5931368.669409.6811985-01- 01201.5231496.843442.913SUMMARY OUTPUT1986-01- 01220.6441597.895462.0341987-01- 01241.7031681.169526.416Regression Statistics1988-01- 01259.3321764.459549.808Multiple R0.7219177861989-01- 01271.3191896.993601.144R Square0.52116528981990-01- 01290.6862055.425620.563Adjusted R Square0.49214500431991-01- 01318.3162166.643617.116Standard Error947.4426158431992- 01-01347.9242339.236645.424Observations361993-01- 01386.3492412.752699.2681994-01- 01423.9242485.781763.463ANOVA1995-01- 01447.8102601.781825.697dfSSMSFSignificance F1996-01- 01466.0032696.964916.958Regression232241083.59348916120 541.796744517.958654830.00000528521997-01- 01494.0472772.3531015.091Residual3329622367.84041198976 47.5103155121998-01- 01525.7842855.5901095.258Total3561863451.43390091999-01- 01575.5602995.8291174.5372000-01- 01607.1773142.0511288.531CoefficientsStandard Errort StatP- valueLower 95%Upper 95%Lower 95.0%Upper 95.0%2001-01- 01641.4893362.4061226.823Intercept- 622.7136666805371.7377431454-1.67514243080.1033585102- 1379.0197917491133.5924583882- 1379.0197917491133.59245838822002-01- 01697.5603585.2061053.184Government expenditures0.48200048630.26381655821.8270289390.0767519 364-0.0547383371.0187393097- 0.0547383371.01873930972003-01- 01741.4423816.0961053.864Tax recipts0.14270963380.9128629180.15633194310.8767238587- 1.71452393741.9999432049-1.71452393741.99994320492004-
  • 14. 01-01777.2814019.4121140.5972005-01- 01806.9934303.4971367.8232006-01- 01835.6784519.9691534.7762007-01- 01851.5924833.6351607.657RESIDUAL OUTPUT2008-01- 011006.4375260.7201489.5162009-01- 011800.0035634.2401123.665ObservationPredicted Monetory baseResiduals2010-01- 012033.9345833.4451273.598195.450761945893.142716315120 11-01- 012540.3875872.1221478.4042161.97345983339.549347859320 12-01- 012665.5895842.4391572.9503213.40920338697.235241057520 13-01-013264.3585854.1241744.8864262.7353283517- 21.03267450552014-01- 013948.9496002.2121900.0555306.2193277903- 46.88748163642015-01- 014008.0876165.9022023.0506377.4270425078- 106.10804250782016-01- 013794.8536377.5802019.3907456.5625014393- 165.87665528542017-01- 013826.0766597.4312019.1638509.677675745- 191.36148343732018-01- 013675.6936930.3841956.0819596.9076018534- 248.98344800732019-01-013315.9070010640.0260947739- 253.677056312311684.3875450866- 260.46342970212749.1808723515- 301.370641582213808.0831181771- 342.079925869414858.4249363336- 364.37841781515909.985729204- 384.201344588616988.8949081427- 413.3350619889171075.6423867507- 468.4653867507181173.0470859843- 531.5585859843191255.6570280987- 558.0974511756201367.0428862653- 625.6006170345211477.4187399592- 700.1372784208221646.7756559007-
  • 15. 839.7825405161231774.9409596373- 939.2634211758241936.5288601851- 1084.9372448005252125.5240942311- 1119.0866127496262253.3503688432- 453.3474842278272370.7642083926- 336.8299776234282418.6345357811121.7523488343292417.81 99269118247.7690730882302447.9887986553816.36962442163 12541.51167451891407.437671635322637.96270021281370.12 39536334332739.46928190271055.3838334819342845.4051400 628980.6710137833352996.8865155542678.806522907436- 622.71366668053938.6209166805 Increase in Monetory base increase government expenditure and Tax reciepts Government expenditures 188.59347826086957 201.52280769230768 220.64444444444445 241.70265384615385 259.33184615384613 271.31900000000002 290.68584615384617 318.31619230769229 347.92415384615384 386.34903846153844 423.92411538461539 447.81023076923077 466.0031923076923 494.0465185185185 525.78438461538462 575.55984615384614 607.17700000000002 641.48850000000004 697.55957692307697 741.44226923076928 777.281461538461 49 806.99311538461541 835.67753846153846 851.59161538461535 1006.4374814814814 1800.0028846153846 2033.9342307692307 2540.3868846153846 2665.5889999999999 3264.3584230769229 3948.9493461538464 4008.0866538461537 3794.8531153846152 3826.0761538461538 3675.6930384615384 3315.9072500000002 1368.66875 1496.8432499999999 1597.895 1681.1692499999999 1764.4590000000001 1896.99325 2055.4250000000002 2166.643 2339.2362499999999
  • 16. 2412.7517499999999 2485.7809999999999 2601.7807499999999 2696.96425 2772.35275 2855.5895 2995.8285000000001 3142.05125 3362.4059999999999 3585.2062500000002 3816.09575 4019.4115000000002 4303.4972500000003 4519.9692500000001 4833.6350000 000002 5260.7197500000002 5634.2394999999997 5833.4447499999997 5872.1222500000003 5842.4390000000003 5854.1237499999997 6002.2122499999996 6165.90175 6377.5797499999999 6597.4307500000004 6930.3842500000001 0 Tax recipts 188.59347826086957 201.52280769230768 220.64444444444445 241.70265384615385 259.33184615384613 271.31900000000002 290.68584615384617 318.31619230769229 347.92415384615384 386.34903846153844 423.92411538461539 447.81023076923077 466.0031923076923 494.0465185185185 525.78438461538462 575.55984615384614 607.17700000000002 641.48850000000004 697.55957692307697 741.44226923076928 777.28146153846149 806.99311538461541 835.67753846153846 851.59161538461535 1006.4374814814814 1800.0028846153846 2033.9342307692307 2540.3868846153846 2665.5889999999999 3264.3584230769229 3948.9493461538464 4008.0866538461537 3794.8531153846152 3826.0761538461538 3675.6930384615384 3315.9072500000002 409.68099999999998 442.91300000000001 462.03399999999999 526.41575 549.80799999999999 601.14400000000001 620.56299999999999 617.11575000000005
  • 17. 645.42425000000003 699.26774999999998 763.46325000000002 825.69725000000005 916.95775000000003 1015.09075 1095.258 1174.5372500000001 1288.53125 1226.82275 1053.18425 1053.864 1140.5965000000001 1367.8232499999999 1534.7755 1607.6567500000001 1489.5160000000001 1123.66525 1273.5977499999999 1478.4034999999999 1572.9502500000001 1744.8855000000001 1900.05475 2023.05 2019.39 2019.16275 1956.0809999999999 0 Monetory Base