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DataAnalysisProject3.xlsxNational Economy
| Increase in Personal income increases consumer expenditures? | ||||
| Observation_date | Personal Income | Consumer expenditures | ||
| 1990-01-01 | 26876 | 4.1 | ||
| 1991-01-01 | 26483 | 3.6 | ||
| 1992-01-01 | 26217 | 3.1 | ||
| 1993-01-01 | 26473 | 2.7 | ||
| 1994-01-01 | 26799 | 2.2 | ||
| 1995-01-01 | 27534 | 2.2 | ||
| 1996-01-01 | 28118 | 1.9 | ||
| 1997-01-01 | 29352 | 1.8 | ||
| 1998-01-01 | 30808 | 1.3 | ||
| 1999-01-01 | 31120 | 1.4 | ||
| 2000-01-01 | 31462 | 1.8 | ||
| 2001-01-01 | 31185 | 1.8 | ||
| 2002-01-01 | 30959 | 1.7 | ||
| 2003-01-01 | 31029 | 1.5 | ||
| 2004-01-01 | 30935 | 2.0 | ||
| 2005-01-01 | 31354 | 2.2 | ||
| 2006-01-01 | 32205 | 2.3 | ||
| 2007-01-01 | 32324 | 2.2 | ||
| 2008-01-01 | 30997 | 2.0 | ||
| 2009-01-01 | 30661 | 1.2 | ||
| 2010-01-01 | 30211 | 1.4 | ||
| 2011-01-01 | 29750 | 1.6 | ||
| 2012-01-01 | 29572 | 1.9 | ||
| 2013-01-01 | 29883 | 1.5 | ||
| 2014-01-01 | 30532 | 1.6 | ||
| 2015-01-01 | 32051 | 1.3 | ||
| 2016-01-01 | 32542 | 1.6 | ||
| 2017-01-01 | 32741 | 1.7 | ||
| 2018-01-01 | 33706 | 1.9 | ||
| Statistical Metrics | ||||
| Mean | 30134 | 2 | ||
| Median | 30808 | 2 | ||
| Sample Variance | 4392205.18965517 | 0.4524368842 | ||
| Standard Deviation | 2095.7588577065 | 0.6726342871 | ||
| Coefficient of Variation | 6.95% | 34.30% | ||
| Max | 33706 | 4 | ||
| Min | 26217 | 1 | ||
| Range | 7489 | 3 | ||
| Percentile | 32367.6 | 2.77 | ||
| Quartile | 29352 | 1.575 | ||
| Skewness | -0.5959228932 | 1.680161164 |
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 Poverty
| Higher Inflation increases the poverty? | ||||
| Observation_date | Inflation rate | Poverty | ||
| 1989-01-01 | 4.2 | 31528020 | ||
| 1990-01-01 | 4.1 | 33875346 | ||
| 1991-01-01 | 3.6 | 35917654 | ||
| 1992-01-01 | 3.1 | 38291114 | ||
| 1993-01-01 | 2.7 | 39264811 | ||
| 1994-01-01 | 2.2 | 37191809 | ||
| 1995-01-01 | 2.2 | 36424609 | ||
| 1996-01-01 | 1.9 | 36529140 | ||
| 1997-01-01 | 1.8 | 35573858 | ||
| 1998-01-01 | 1.3 | 34475762 | ||
| 1999-01-01 | 1.4 | 32791272 | ||
| 2000-01-01 | 1.8 | 31581086 | ||
| 2001-01-01 | 1.8 | 32906511 | ||
| 2002-01-01 | 1.7 | 34569951 | ||
| 2003-01-01 | 1.5 | 35861170 | ||
| 2004-01-01 | 2.0 | 37039804 | ||
| 2005-01-01 | 2.2 | 38231474 | ||
| 2006-01-01 | 2.3 | 38757253 | ||
| 2007-01-01 | 2.2 | 38052247 | ||
| 2008-01-01 | 2.0 | 39108422 | ||
| 2009-01-01 | 1.2 | 42868163 | ||
| 2010-01-01 | 1.4 | 46215956 | ||
| 2011-01-01 | 1.6 | 48452035 | ||
| 2012-01-01 | 1.9 | 48760123 | ||
| 2013-01-01 | 1.5 | 48810868 | ||
| 2014-01-01 | 1.6 | 48208387 | ||
| 2015-01-01 | 1.3 | 46153077 | ||
| 2016-01-01 | 1.6 | 44268996 | ||
| 2017-01-01 | 1.7 | 42583651 | ||
| Statistical Metrics | ||||
| Mean | 2.0379310345 | 39113536.862069 | ||
| Median | 1.775 | 38052247 | ||
| Sample Variance | 0.6173937808 | 29644929955060.6 | ||
| Standard Deviation | 0.7857440937 | 5444715.78276227 | ||
| Coefficient of Variation | 39% | 14% | ||
| Max | 4.15 | 48810868 | ||
| Min | 1.15 | 31528020 | ||
| Range | 3 | 17282848 | ||
| Percentile | 3.155 | 48257116.6 | ||
| Quitiles | 1.575 | 35573858 | ||
| Skewness | 1.5675196079 | 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 Name | Sales ($) (Billions) | Profits ($) (Billions) | ||
| ICBC | 179.5 | 45.2 | ||
| JP Morgan Chase | 132.9 | 32.7 | ||
| China construction bank | 150.3 | 38.8 | ||
| Agriculture Bank of China | 137.5 | 30.9 | ||
| Bank of America | 111.9 | 28.5 | ||
| Apple | 261.7 | 59.4 | ||
| Ping An Insurance Group | 151.8 | 16.3 | ||
| Bank of China | 126.7 | 27.5 | ||
| Royal Dutch Shell | 382.6 | 23.3 | ||
| Wells Fargo | 101.5 | 23.1 | ||
| Exxon Mobil | 279.2 | 20.8 | ||
| AT&T | 170.8 | 19.4 | ||
| Samsung Electronics | 221.5 | 39.9 | ||
| citigroup | 100 | 17.9 | ||
| toyota motor | 272.1 | 17.2 | ||
| microsoft | 118.2 | 33.5 | ||
| alphabet | 137 | 30.7 | ||
| volkswagen group | 278.2 | 14 | ||
| chevron | 158.7 | 14.8 | ||
| verizon communications | 130.9 | 15.5 | ||
| HSBC holdings | 64.3 | 13.7 | ||
| petro china | 322.8 | 8 | ||
| allianz | 118.8 | 8.8 | ||
| BP | 299.1 | 9.3 | ||
| total | 184.2 | 11.4 | ||
| berkshire hathaway | 247.8 | 4 | ||
| china mobile | 111.8 | 17.9 | ||
| amazon | 232.9 | 10.1 | ||
| walmart | 514.4 | 6.7 | ||
| santander | 89.5 | 9.2 | ||
| Statistical Metrics | ||||
| Mean | 192.9533333333 | 21.6166666667 | ||
| Median | 155.25 | 17.9 | ||
| Sample Variance | 10018.0418850575 | 167.0359195402 | ||
| Standard Deviation | 100.0901687732 | 12.9242376773 | ||
| Coefficient of Variation | 52% | 60% | ||
| Max | 514.4 | 59.4 | ||
| Min | 64.3 | 4 | ||
| Range | 450.1 | 55.4 | ||
| Percentile | 301.47 | 38.91 | ||
| Quitiles | 120.775 | 11.975 | ||
| Skewness | 1.3914372868 | 1.0566186151 | ||
| Single Regression | ||||
| Sales ($) (Billions) | Profits ($) (Billions) | |||
| Sales ($) (Billions) | 1 | |||
| Profits ($) (Billions) | -0.1803817608 | 1 | ||
| Multiple 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 Statistics
| High wages and salaries high compensation？ | ||||
| Observation Date | Wages and Salaries | Compensation | ||
| 2001-01-01 | 88.8 | 6039.136 | ||
| 2002-01-01 | 91.7 | 6135.569 | ||
| 2003-01-01 | 94.3 | 6354.054 | ||
| 2004-01-01 | 96.8 | 6720.058 | ||
| 2005-01-01 | 99.2 | 7066.605 | ||
| 2006-01-01 | 102.1 | 7479.895 | ||
| 2007-01-01 | 105.5 | 7878.862 | ||
| 2008-01-01 | 108.6 | 8056.978 | ||
| 2009-01-01 | 110.4 | 7758.509 | ||
| 2010-01-01 | 112.1 | 7924.936 | ||
| 2011-01-01 | 114.0 | 8225.931 | ||
| 2012-01-01 | 116.0 | 8566.725 | ||
| 2013-01-01 | 118.2 | 8834.222 | ||
| 2014-01-01 | 120.6 | 9249.097 | ||
| 2015-01-01 | 123.3 | 9698.155 | ||
| 2016-01-01 | 126.3 | 9960.324 | ||
| 2017-01-01 | 129.5 | 10411.610 | ||
| 2018-01-01 | 133.4 | 10928.452 | ||
| Statistical Metrics | ||||
| Mean | 110.6 | 8182.7 | ||
| Median | 111.2 | 7991.0 | ||
| Sample Variance | 177.2458986928 | 2119868.16933351 | ||
| Standard Deviation | 13.313372927 | 1455.9767063156 | ||
| Coefficient of Variation | 12% | 18% | ||
| Max | 133.4 | 10928.5 | ||
| Min | 88.8 | 6039.1 | ||
| Range | 44.6 | 4889.3 | ||
| Percentile | 127.225 | 10095.7098 | ||
| Quitiles | 99.875 | 7169.9275 | ||
| Skewness | -0.0051840429 | 0.276182045 |
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
Government
| Increase in Monetory base increases government expenditures and tax reciepts？ | ||||||||||||||||
| Observation_date | Monetory base | Government expenditures | Tax recipts | |||||||||||||
| 1984-01-01 | 188.593 | 1368.669 | 409.681 | |||||||||||||
| 1985-01-01 | 201.523 | 1496.843 | 442.913 | SUMMARY OUTPUT | ||||||||||||
| 1986-01-01 | 220.644 | 1597.895 | 462.034 | |||||||||||||
| 1987-01-01 | 241.703 | 1681.169 | 526.416 | Regression Statistics | ||||||||||||
| 1988-01-01 | 259.332 | 1764.459 | 549.808 | Multiple R | 0.721917786 | |||||||||||
| 1989-01-01 | 271.319 | 1896.993 | 601.144 | R Square | 0.5211652898 | |||||||||||
| 1990-01-01 | 290.686 | 2055.425 | 620.563 | Adjusted R Square | 0.4921450043 | |||||||||||
| 1991-01-01 | 318.316 | 2166.643 | 617.116 | Standard Error | 947.442615843 | |||||||||||
| 1992-01-01 | 347.924 | 2339.236 | 645.424 | Observations | 36 | |||||||||||
| 1993-01-01 | 386.349 | 2412.752 | 699.268 | |||||||||||||
| 1994-01-01 | 423.924 | 2485.781 | 763.463 | ANOVA | ||||||||||||
| 1995-01-01 | 447.810 | 2601.781 | 825.697 | df | SS | MS | F | Significance F | ||||||||
| 1996-01-01 | 466.003 | 2696.964 | 916.958 | Regression | 2 | 32241083.593489 | 16120541.7967445 | 17.95865483 | 0.0000052852 | |||||||
| 1997-01-01 | 494.047 | 2772.353 | 1015.091 | Residual | 33 | 29622367.8404119 | 897647.510315512 | |||||||||
| 1998-01-01 | 525.784 | 2855.590 | 1095.258 | Total | 35 | 61863451.4339009 | ||||||||||
| 1999-01-01 | 575.560 | 2995.829 | 1174.537 | |||||||||||||
| 2000-01-01 | 607.177 | 3142.051 | 1288.531 | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |||||
| 2001-01-01 | 641.489 | 3362.406 | 1226.823 | Intercept | -622.7136666805 | 371.7377431454 | -1.6751424308 | 0.1033585102 | -1379.0197917491 | 133.5924583882 | -1379.0197917491 | 133.5924583882 | ||||
| 2002-01-01 | 697.560 | 3585.206 | 1053.184 | Government expenditures | 0.4820004863 | 0.2638165582 | 1.827028939 | 0.0767519364 | -0.054738337 | 1.0187393097 | -0.054738337 | 1.0187393097 | ||||
| 2003-01-01 | 741.442 | 3816.096 | 1053.864 | Tax recipts | 0.1427096338 | 0.912862918 | 0.1563319431 | 0.8767238587 | -1.7145239374 | 1.9999432049 | -1.7145239374 | 1.9999432049 | ||||
| 2004-01-01 | 777.281 | 4019.412 | 1140.597 | |||||||||||||
| 2005-01-01 | 806.993 | 4303.497 | 1367.823 | |||||||||||||
| 2006-01-01 | 835.678 | 4519.969 | 1534.776 | |||||||||||||
| 2007-01-01 | 851.592 | 4833.635 | 1607.657 | RESIDUAL OUTPUT | ||||||||||||
| 2008-01-01 | 1006.437 | 5260.720 | 1489.516 | |||||||||||||
| 2009-01-01 | 1800.003 | 5634.240 | 1123.665 | Observation | Predicted Monetory base | Residuals | ||||||||||
| 2010-01-01 | 2033.934 | 5833.445 | 1273.598 | 1 | 95.4507619458 | 93.1427163151 | ||||||||||
| 2011-01-01 | 2540.387 | 5872.122 | 1478.404 | 2 | 161.973459833 | 39.5493478593 | ||||||||||
| 2012-01-01 | 2665.589 | 5842.439 | 1572.950 | 3 | 213.4092033869 | 7.2352410575 | ||||||||||
| 2013-01-01 | 3264.358 | 5854.124 | 1744.886 | 4 | 262.7353283517 | -21.0326745055 | ||||||||||
| 2014-01-01 | 3948.949 | 6002.212 | 1900.055 | 5 | 306.2193277903 | -46.8874816364 | ||||||||||
| 2015-01-01 | 4008.087 | 6165.902 | 2023.050 | 6 | 377.4270425078 | -106.1080425078 | ||||||||||
| 2016-01-01 | 3794.853 | 6377.580 | 2019.390 | 7 | 456.5625014393 | -165.8766552854 | ||||||||||
| 2017-01-01 | 3826.076 | 6597.431 | 2019.163 | 8 | 509.677675745 | -191.3614834373 | ||||||||||
| 2018-01-01 | 3675.693 | 6930.384 | 1956.081 | 9 | 596.9076018534 | -248.9834480073 | ||||||||||
| 2019-01-01 | 3315.907 | 0 | 0 | 10 | 640.0260947739 | -253.6770563123 | ||||||||||
| 11 | 684.3875450866 | -260.463429702 | ||||||||||||||
| 12 | 749.1808723515 | -301.3706415822 | ||||||||||||||
| 13 | 808.0831181771 | -342.0799258694 | ||||||||||||||
| 14 | 858.4249363336 | -364.378417815 | ||||||||||||||
| 15 | 909.985729204 | -384.2013445886 | ||||||||||||||
| 16 | 988.8949081427 | -413.3350619889 | ||||||||||||||
| 17 | 1075.6423867507 | -468.4653867507 | ||||||||||||||
| 18 | 1173.0470859843 | -531.5585859843 | ||||||||||||||
| 19 | 1255.6570280987 | -558.0974511756 | ||||||||||||||
| 20 | 1367.0428862653 | -625.6006170345 | ||||||||||||||
| 21 | 1477.4187399592 | -700.1372784208 | ||||||||||||||
| 22 | 1646.7756559007 | -839.7825405161 | ||||||||||||||
| 23 | 1774.9409596373 | -939.2634211758 | ||||||||||||||
| 24 | 1936.5288601851 | -1084.9372448005 | ||||||||||||||
| 25 | 2125.5240942311 | -1119.0866127496 | ||||||||||||||
| 26 | 2253.3503688432 | -453.3474842278 | ||||||||||||||
| 27 | 2370.7642083926 | -336.8299776234 | ||||||||||||||
| 28 | 2418.6345357811 | 121.7523488343 | ||||||||||||||
| 29 | 2417.8199269118 | 247.7690730882 | ||||||||||||||
| 30 | 2447.9887986553 | 816.3696244216 | ||||||||||||||
| 31 | 2541.5116745189 | 1407.437671635 | ||||||||||||||
| 32 | 2637.9627002128 | 1370.1239536334 | ||||||||||||||
| 33 | 2739.4692819027 | 1055.3838334819 | ||||||||||||||
| 34 | 2845.4051400628 | 980.6710137833 | ||||||||||||||
| 35 | 2996.8865155542 | 678.8065229074 | ||||||||||||||
| 36 | -622.7136666805 | 3938.6209166805 |
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
