Use the same regression results where you already found R square and other results for this regression. What is the standard error for the estimated slope of the regression line?

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Use the same regression results where you already found R square and other results for this regression. What is the standard error for the estimated slope of the regression line?

8 AutoSave D The Home Data Review View Help Power Pivot Formulas Insert Draw Page Layout ES - per capita GDP 1 Country Name 2
1447.222821 1282437162 238304473 1759.192902 2108 M1038 783.0111438 1827.101.168 1689.991818 2620 262052 3623.51236 1675.7475
Home Insert Draw Page Layout Forms Data VW VW PU U L 3998.739499 590052957 4179.597681 5226090303 6882.406872 494.991625 5195
AS 28 worldbank.122020 - Lace E Home incent Dron Page Layout Formulas Data Revira v ou Help Power Post 999 629 10975. 3 11 So
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0.5 pts Question 9 Use the same regression results where you already found R square and other results for this regression. Wh
8 AutoSave D The Home Data Review View Help Power Pivot Formulas Insert Draw Page Layout ES – per capita GDP 1 Country Name 2 Central African Republic 3 Myanmar 4 Congo, Dem. Rep. 5 South Sudan 6 Madagascar 7 Burundi 8 Ethiopia 9 Guinea 10 Malawi 11 Niger 12 Gambia, The 13 Bangladesh 14 Guinea-Bissau 15 Lao PDR 16 Benin 17 Pakistan 18 Chad 19 Nepal 20 Mozambique 21 uberia 22 Kenya 23 Senegal 24 Burkina Faso 25 Mauritania per capita spending on healthcare 326.4371085 13.0093878 1106.983824 14.4014357 413.6970577 15.91195894 1157.486958 18.07399793 19.63129425 462.979991 259.3652087 21.46176493 5039026066 24.51864915 521.5389069 24.75235174 239.8697314 26.21476794 418492422 272310651 154.1126819 28.91017917 9543963997 316113186 538.7338705 31. 037079 1700.987378 32.40633912 8826186333 36.69098125 1275, 363548 36.87768141 985.0952473 37.20064104 692. 363094 39.0262313 6052344447 40.255418427 453.339457 44.37100005 1257.202835 44,50922542 1051176421 45.55016602 208.8416819 45.640052 1806.007652 AR 39684196 910.3792327 796.7645736 659.5201611 53.28703339 626.1728645 666.7950511 1117.731251 SR042924 62.3416307 1455.102191 61.40821315 1331 200021 67.17278529 1043.659569 31 Timor-Leste 1 Uganda 33 India 34 Cameroon 35 Takistan Rwanda 37 Yemen, Rep 38 Cambodia 39 Mai 40 Cote d’Ivoire 41 Kyrgy Republic Healthcare Regression R10.3265496 85.7557136 data © Type here to search
1447.222821 1282437162 238304473 1759.192902 2108 M1038 783.0111438 1827.101.168 1689.991818 2620 262052 3623.51236 1675.747572 1908.64034 1726080156 2979.834679 1672.564512 27690068 3167.055303 1064,828322 36.75579136 36.50594123 89. 249 92.81073153 93.83476237 95.8328 107 99.5246516 100.2731974 109.4151403 106.61M79 101.9795682 111.1695022 114.95.2551 114.9669057 40 Cote d’Ivoire 41 Kyrgyz Republic 42 Bhutan 43 Zambia 44 Papua New Guinea 45 Sierra Leone 46 Ghana 47 Solomon Islands 48 Sri Lanka 49 Indonesia So Sao Tome and Principe 51 Vietnam 52 Sudan 53 Nigeria 54 Urbekistan 55 Philippines 56 Vanuatu 57 Lesotho 58 Congo, Rep. 59 Dibouti 50 Ceypt, Arab Rep. 61 Nicaragua 62 Turkmenistan 63 Armenia Cabo Verde 65 Wibati 66 Bolivia 67 F 68 Morocco 9 Honduras 70 Tonga 71 Guatemala 72 Albania 73 Mongolia T4 Guyana 75 Swartland 121.5959221 123.162335 123.4M482 110.7115615 137.3641429 151.2641386 163429923 2104219707 1894988076 157.5401463 15.6215569 155652577 M18.032916 46.997 342.022106 4362.07056 4713.137305 200146276 6229. 1726.56 TT Moldova 78 Thailand 79 Salvador 80 Angola S757 P Type here to search
Home Insert Draw Page Layout Forms Data VW VW PU U L 3998.739499 590052957 4179.597681 5226090303 6882.406872 494.991625 5195.28488 4029.715504 5491.614414 596.69476 5924.836131 5200 205197 6501.56649 265.7710897 267.2242988 270.7399126 304.6260753 3053529361 30R 56.168 312.3879955 312.612556 313.5202115 314,5126078 328.50017 335.7551655 3449056111 349.9031357 334212 366.86302 19.9596666 397.3182644 6603.09596 6991.853866 4497.435166 79 El Salvador 80 Angola 81 Samoa 82 Jamaica 83 trag 54 Tunisia BS Macedonia, FYR 36 Ukraine 87 Algeria Dominican Republic 89 Small states 90 Jordan 91 St. Vincent and the Grenadine 92 Georgia 93 Peru 94 China 95 Paraguay 96 Botswana 97 Micronesia, Fed. Sts. 98 Dominica 99 Namibia 100 Malaysia 101 Ecuador 102 tran, Islamic Rep. 103 Libya 104 Azerbaijan 105 Gabon 106 Suriname 107 Bosnia and Herzegovina 10 Montenegro 19 Mauritius 110 Belarus 111 Serbia 112 Grenada 11 Romania 114 Colombia 115 Seychelles 116 Bulgaria 117 khan South Africa 3001077373 7036.5438 10971.65594 5051.611129 663129827 10454.79355 417.2184.202 422.5836885 473.4301212 411.0725731 4322176 437. 2303 416027778 9618. 150531 666.219586 418.7591504 7722.123351 971777 603.3629.228 67.49597 I Type here to search
AS 28 worldbank.122020 – Lace E Home incent Dron Page Layout Formulas Data Revira v ou Help Power Post 999 629 10975. 3 11 South Africa 119 Cuba 120 Turkey 1:21 St. Lucia 122 Marshall Islands 123 Lebanon 591.4541967 SO 228 607,2022196 621. 2012 GON 102 0. 42 10172.72355 Barbuda 129 And 126 Oman 127 Tuvalu 20011 62 7040M52 2143 049 12 Maldives 1 Panama Saudi Arabia 12 stund Nevis 133 Latvia 114 Poland 156252 23 11th 17 Brunei Darussalam Croatia VISU 981510 141 Barbados 100.215496 1903 10 144. Bahan 145 Estonia 15 na 1914.4212 130 143 Chile 149 Crech Republic 151 Show Republic 15 United Arab Emirates 15e/Cyprus 6737
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0.5 pts Question 9 Use the same regression results where you already found R square and other results for this regression. What is the standard error for the estimated slope of the regression line? Answer to four decimal places 0.5 pts Question 10 Using the same regression results what is the estimated coefficient on per capita GDP? Answer to three decimal places. Question 11 0.5 pts Based on your regression results and your answer in the previous question using the World Bank data what happens to per capita expenditure on health care as per capita GDP increases? The total expenditure decreases As the per capita GDP increase people are healthier and so they spend less on health care on average None of the other answers are correct. The expenditure increases. As per capita GDP increases people tend to spend more on health care. The total expenditure stays constant because as the price increases the amount people buy stays the same

 


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