From Last HW
Reading in the Dataset & Cleaining
SPI <- read_excel("/Users/karenkimble/Documents/R Practice/Social Progress Index.xlsx", sheet = "2011-2021 data")
SPI$...10 <- NULL
SPI$...23 <- NULL
colnames(SPI) <- c("Rank",
"Country",
"Code",
"Year",
"Status",
"SPI",
"Needs",
"Wellbeing",
"Opportunity",
"Nutrition/care",
"Sanitation",
"Shelter",
"Safety",
"Access-knowledge",
"Info-comm",
"Health",
"Environment",
"Rights",
"Choice",
"Inclusiveness",
"Advanced-ed",
"Infectious",
"Child mortality",
"Stunting",
"Maternal-mortality",
"Undernourishment",
"Improved-sanitation",
"Improved-water",
"Hygeine-deaths",
"Pollution-deaths",
"Housing",
"Electricity",
"Clean-fuels",
"Personal-violence-deaths",
"Transport",
"Criminality",
"Political-killings",
"Women-no-education",
"Education-access",
"Primary-enrollment",
"Secondary-attainment",
"Gender-gap-secondary",
"Online-governance",
"Internet-users",
"Media",
"Cellphone",
"Life-expectancy",
"Premature-deaths",
"Healthcare",
"Essential-services",
"Pollution",
"Lead",
"Particulate",
"Species",
"Justice",
"Expression",
"Religion",
"Political-rights",
"Property",
"Contraception",
"Corruption",
"Early-marriage",
"Youth-nonemployed",
"Vulnerable",
"Equal-gender",
"Equal-social",
"Equal-socioeconomic",
"Discrimination-violence",
"LGBT",
"Citable-docs",
"Academic",
"Women-advanced",
"Tertiary",
"Quality-unis")
View(SPI)
Summary Statistics
Because of the sheer amount of variables within this dataset, I will be only be focusing on one category of the SPI’s three major categories: Foundations of Wellbeing. The other two categories, Basic Needs and Opportunity, are still important and should be analyzed. However, I am primarily interested in the Foundations of Wellbeing category, which includes indicators related to access to knowledge and infrastructure as well as health, because it may be interesting to see if countries generally viewed as more “free” and democratic will do well in those categories (such as the United States or some European Union countries). There are still a lot of variables condensed into the Foundations of Wellbeing category, so I will analyze the main variables that are computed using their sub-categories. Those variables are: Access to Basic Knowledge, Access to Information and Communications, Health and Wellness, and Environmental Quality.
Country N Access-knowledge sd
1 Albania 11 89.79818 3.1898929
2 Algeria 11 73.41818 3.2575287
3 American Samoa 11 NA NA
4 Andorra 11 NA NA
5 Angola 11 47.80091 1.8826548
6 Antigua and Barbuda 11 NA NA
7 Argentina 11 84.57364 0.5987699
8 Armenia 11 93.78636 1.5730180
9 Australia 11 94.97636 0.6425300
10 Austria 11 96.26636 1.1831352
11 Azerbaijan 11 85.30364 3.0429438
12 Bahamas, The 11 NA NA
13 Bahrain 11 77.95364 2.5489735
14 Bangladesh 11 60.45364 2.9819138
15 Barbados 11 96.01364 0.8422151
16 Belarus 11 95.25636 0.7660843
17 Belgium 11 94.14364 0.7445041
18 Belize 11 NA NA
19 Benin 11 52.16636 3.1420294
20 Bermuda 11 NA NA
21 Bhutan 11 53.04455 6.8126403
22 Bolivia 11 70.06636 2.1988965
23 Bosnia and Herzegovina 11 80.52182 4.6330961
24 Botswana 11 82.61182 1.6348192
25 Brazil 11 75.58091 2.1845756
26 Brunei Darussalam 11 NA NA
27 Bulgaria 11 90.19091 2.8178053
28 Burkina Faso 11 28.23455 3.6659199
29 Burundi 11 46.74364 1.6398003
30 Cabo Verde 11 66.96454 1.2442933
31 Cambodia 11 51.12000 1.4666699
32 Cameroon 11 66.68818 2.5475587
33 Canada 11 97.32727 0.7464722
34 Central African Republic 11 32.72818 1.9290561
35 Chad 11 21.04273 3.2559638
36 Chile 11 82.85545 0.8516839
37 China 11 77.60091 2.4908683
38 Colombia 11 77.09364 0.5161632
39 Comoros 11 55.27182 2.6230702
40 Congo, Democratic Republic of 11 55.69000 5.0903303
41 Congo, Republic of 11 67.68727 2.7058497
42 Cook Islands 11 NA NA
43 Costa Rica 11 87.01182 0.5798246
44 Côte d'Ivoire 11 38.18000 7.8408790
45 Croatia 11 94.54364 2.3721861
46 Cuba 11 90.98273 1.4826065
47 Cyprus 11 93.33818 0.8828463
48 Czechia 11 98.36364 0.1183436
49 Denmark 11 97.93818 0.6199972
50 Djibouti 11 34.25909 2.8588648
51 Dominica 11 NA NA
52 Dominican Republic 11 73.93637 0.3824727
53 Ecuador 11 82.96364 0.6525989
54 Egypt 11 71.58182 3.8042176
55 El Salvador 11 66.38091 1.6720138
56 Equatorial Guinea 11 47.25273 1.5509615
57 Eritrea 11 42.52091 1.8703506
58 Estonia 11 98.62000 0.3100956
59 Eswatini 11 65.63818 2.0045398
60 Ethiopia 11 41.31364 4.3955101
61 Fiji 11 87.37273 1.5355983
62 Finland 11 98.55273 1.2356143
63 France 11 93.34000 0.5977782
64 Gabon 11 68.42091 4.8518977
65 Gambia, The 11 43.41818 7.0232442
66 Georgia 11 94.75182 0.4048402
67 Germany 11 96.71182 0.6264156
68 Ghana 11 65.77727 4.0763029
69 Greece 11 89.03273 0.8496954
70 Greenland 11 NA NA
71 Grenada 11 NA NA
72 Guam 11 NA NA
73 Guatemala 11 62.89909 3.4238534
74 Guinea 11 27.37364 2.8190330
75 Guinea-Bissau 11 33.50273 5.0061927
76 Guyana 11 77.53636 1.1825262
77 Haiti 11 49.62909 1.9104476
78 Honduras 11 61.61364 1.4538381
79 Hong Kong 11 NA NA
80 Hungary 11 92.80545 0.9842897
81 Iceland 11 98.81182 0.5468438
82 India 11 56.30727 1.6813394
83 Indonesia 11 71.77818 0.8722603
84 Iran 11 78.95909 2.2459624
85 Iraq 11 56.56182 3.4374255
86 Ireland 11 94.76455 0.6217297
87 Israel 11 89.79636 0.5203317
88 Italy 11 90.72273 0.5348841
89 Jamaica 11 84.65727 1.0090885
90 Japan 11 97.95546 0.5169404
91 Jordan 11 77.66909 1.6497659
92 Kazakhstan 11 94.64818 0.1691642
93 Kenya 11 63.73000 0.3682925
94 Kiribati 11 NA NA
95 Korea, Democratic Republic of 11 NA NA
96 Korea, Republic of 11 91.35364 0.5454401
97 Kosovo 11 NA NA
98 Kuwait 11 81.92364 1.9457662
99 Kyrgyzstan 11 92.10909 0.9374164
100 Laos 11 58.59182 2.4654774
101 Latvia 11 96.46818 0.8043855
102 Lebanon 11 80.73636 0.5364010
103 Lesotho 11 76.10182 1.2572495
104 Liberia 11 44.93000 1.5343791
105 Libya 11 62.19909 1.5775205
106 Lithuania 11 96.18818 0.3730091
107 Luxembourg 11 98.16364 0.7734754
108 Madagascar 11 63.54545 2.1821347
109 Malawi 11 55.69455 3.1616776
110 Malaysia 11 85.58182 2.6139208
111 Maldives 11 68.70909 2.2634389
112 Mali 11 26.09727 1.6474717
113 Malta 11 91.71454 1.6295296
114 Marshall Islands 11 NA NA
115 Mauritania 11 39.21273 2.9702826
116 Mauritius 11 85.49545 2.4047551
117 Mexico 11 77.31545 1.8511533
118 Micronesia 11 NA NA
119 Moldova 11 90.54727 0.6694048
120 Monaco 11 NA NA
121 Mongolia 11 90.93545 0.4904158
122 Montenegro 11 92.69182 0.7585349
123 Morocco 11 55.51636 4.0032121
124 Mozambique 11 46.31182 6.0665834
125 Myanmar 11 57.31455 5.5425800
126 Namibia 11 73.05818 1.6786545
127 Nauru 11 NA NA
128 Nepal 11 49.95000 3.2891974
129 Netherlands 11 95.09545 0.7414631
130 New Zealand 11 97.34909 0.6794617
131 Nicaragua 11 73.49818 2.0631182
132 Niger 11 21.13000 3.4109381
133 Nigeria 11 49.88182 2.3846207
134 Niue 11 NA NA
135 Northern Mariana Islands 11 NA NA
136 Norway 11 98.66091 0.2333431
137 Oman 11 77.48455 1.6266374
138 Pakistan 11 41.52364 3.1799188
139 Palau 11 NA NA
140 Panama 11 81.32818 1.0672942
141 Papua New Guinea 11 46.62545 1.8081062
142 Paraguay 11 69.89091 1.9347467
143 Peru 11 75.81364 1.2504335
144 Philippines 11 80.04364 1.0685346
145 Poland 11 93.09909 0.7963838
146 Portugal 11 87.86636 0.9745901
147 Puerto Rico 11 NA NA
148 Qatar 11 83.17182 2.1946930
149 Republic of North Macedonia 11 75.93909 1.1403204
150 Romania 11 86.54091 2.8033038
151 Russia 11 93.60545 0.6037760
152 Rwanda 11 61.28545 2.7062317
153 Samoa 11 NA NA
154 San Marino 11 NA NA
155 Sao Tome and Principe 11 65.57546 1.5987940
156 Saudi Arabia 11 77.75636 4.0028228
157 Senegal 11 37.19727 1.4542972
158 Serbia 11 90.46273 1.4031544
159 Seychelles 11 89.83454 0.6601571
160 Sierra Leone 11 48.22545 3.2533839
161 Singapore 11 89.82636 0.9552942
162 Slovakia 11 91.71455 0.3828145
163 Slovenia 11 98.49455 1.0611638
164 Solomon Islands 11 58.43909 3.1295279
165 Somalia 11 22.59364 1.5078151
166 South Africa 11 78.82091 1.0600900
167 South Sudan 11 27.33000 0.7296301
168 Spain 11 88.57636 0.7425805
169 Sri Lanka 11 86.73636 1.8138483
170 St Kitts and Nevis 11 NA NA
171 St Lucia 11 NA NA
172 St Vincent and the Grenadines 11 NA NA
173 Sudan 11 37.41818 3.6240663
174 Suriname 11 77.58182 0.6612527
175 Sweden 11 94.03273 0.5843824
176 Switzerland 11 98.43182 0.3782009
177 Syria 11 58.80273 4.4209420
178 Taiwan 11 NA NA
179 Tajikistan 11 86.74545 1.0454701
180 Tanzania 11 55.89909 2.8227411
181 Thailand 11 76.45818 0.6688022
182 Timor-Leste 11 54.37636 2.8325259
183 Togo 11 57.54364 2.5228202
184 Tokelau 11 NA NA
185 Tonga 11 NA NA
186 Trinidad and Tobago 11 89.90818 0.9800383
187 Tunisia 11 68.89909 1.9695662
188 Turkey 11 70.29636 2.0020760
189 Turkmenistan 11 86.37455 1.4286252
190 Tuvalu 11 NA NA
191 Uganda 11 62.76091 2.5668956
192 Ukraine 11 91.76455 1.0896826
193 United Arab Emirates 11 83.81091 3.7595050
194 United Kingdom 11 93.35727 1.6374017
195 United States 11 92.78273 0.2913448
196 Uruguay 11 86.29182 0.7359989
197 Uzbekistan 11 92.58545 0.9629567
198 Vanuatu 11 75.14818 0.8629345
199 Vietnam 11 85.38636 0.7787330
200 Virgin Islands (US) 11 NA NA
201 West Bank and Gaza 11 81.50818 4.0646287
202 World 11 70.50636 1.3558634
203 Yemen 11 37.02091 4.1719048
204 Zambia 11 59.87909 1.7431725
205 Zimbabwe 11 79.00091 1.7164705
se ci
1 0.96178890 2.14299922
2 0.98218185 2.18843753
3 NA NA
4 NA NA
5 0.56764178 1.26478470
6 NA NA
7 0.18053592 0.40225910
8 0.47428277 1.05676786
9 0.19373008 0.43165753
10 0.35672869 0.79484104
11 0.91748208 2.04427747
12 NA NA
13 0.76854443 1.71242370
14 0.89908084 2.00327696
15 0.25393741 0.56580781
16 0.23098311 0.51466244
17 0.22447642 0.50016463
18 NA NA
19 0.94735750 2.11084405
20 NA NA
21 2.05408833 4.57679401
22 0.66299225 1.47723879
23 1.39693103 3.11255631
24 0.49291655 1.09828651
25 0.65867432 1.46761784
26 NA NA
27 0.84960027 1.89302738
28 1.10531644 2.46279850
29 0.49441841 1.10163286
30 0.37516854 0.83592759
31 0.44221761 0.98532224
32 0.76811784 1.71147320
33 0.22506985 0.50148687
34 0.58163231 1.29595755
35 0.98171003 2.18738627
36 0.25679236 0.57216903
37 0.75102504 1.67338807
38 0.15562906 0.34676316
39 0.79088541 1.76220251
40 1.53479232 3.41973040
41 0.81584438 1.81781455
42 NA NA
43 0.17482370 0.38953147
44 2.36411397 5.26757419
45 0.71524102 1.59365631
46 0.44702267 0.99602858
47 0.26618818 0.59310423
48 0.03568193 0.07950429
49 0.18693620 0.41651980
50 0.86198016 1.92061148
51 NA NA
52 0.11531986 0.25694867
53 0.19676598 0.43842192
54 1.14701477 2.55570818
55 0.50413112 1.12327414
56 0.46763248 1.04195009
57 0.56393191 1.25651860
58 0.09349735 0.20832509
59 0.60439148 1.34666813
60 1.32529616 2.95294386
61 0.46300031 1.03162897
62 0.37255173 0.83009698
63 0.18023690 0.40159284
64 1.46290219 3.25954920
65 2.11758780 4.71827965
66 0.12206392 0.27197536
67 0.18887141 0.42083173
68 1.22905158 2.73849758
69 0.25619280 0.57083314
70 NA NA
71 NA NA
72 NA NA
73 1.03233066 2.30017604
74 0.84997042 1.89385212
75 1.50942390 3.36320604
76 0.35654507 0.79443193
77 0.57602162 1.28345615
78 0.43834867 0.97670170
79 NA NA
80 0.29677451 0.66125481
81 0.16487960 0.36737464
82 0.50694291 1.12953919
83 0.26299637 0.58599243
84 0.67718313 1.50885805
85 1.03642278 2.30929386
86 0.18745856 0.41768371
87 0.15688592 0.34956362
88 0.16127363 0.35934004
89 0.30425162 0.67791486
90 0.15586339 0.34728526
91 0.49742313 1.10832781
92 0.05100493 0.11364607
93 0.11104437 0.24742228
94 NA NA
95 NA NA
96 0.16445637 0.36643163
97 NA NA
98 0.58667059 1.30718353
99 0.28264169 0.62976493
100 0.74336939 1.65633023
101 0.24253134 0.54039350
102 0.16173098 0.36035908
103 0.37907500 0.84463174
104 0.46263270 1.03080990
105 0.47564033 1.05979270
106 0.11246647 0.25059091
107 0.23321162 0.51962787
108 0.65793836 1.46597802
109 0.95328167 2.12404393
110 0.78812676 1.75605586
111 0.68245252 1.52059897
112 0.49673139 1.10678652
113 0.49132167 1.09473291
114 NA NA
115 0.89557389 1.99546298
116 0.72506094 1.61553645
117 0.55814371 1.24362169
118 NA NA
119 0.20183314 0.44971225
120 NA NA
121 0.14786593 0.32946581
122 0.22870687 0.50959067
123 1.20701386 2.68939447
124 1.82914371 4.07558616
125 1.67115076 3.72355593
126 0.50613337 1.12773543
127 NA NA
128 0.99173033 2.20971287
129 0.22355954 0.49812170
130 0.20486541 0.45646858
131 0.62205354 1.38602166
132 1.02843654 2.29149941
133 0.71899020 1.60201000
134 NA NA
135 NA NA
136 0.07035560 0.15676205
137 0.49044962 1.09278984
138 0.95878160 2.13629852
139 NA NA
140 0.32180130 0.71701798
141 0.54516455 1.21470231
142 0.58334808 1.29978051
143 0.37701988 0.84005265
144 0.32217530 0.71785129
145 0.24011874 0.53501789
146 0.29384997 0.65473853
147 NA NA
148 0.66172484 1.47441482
149 0.34381953 0.76607765
150 0.84522789 1.88328509
151 0.18204530 0.40562220
152 0.81595957 1.81807121
153 NA NA
154 NA NA
155 0.48205454 1.07408444
156 1.20689648 2.68913294
157 0.43848710 0.97701014
158 0.42306696 0.94265193
159 0.19904487 0.44349960
160 0.98093216 2.18565306
161 0.28803203 0.64177536
162 0.11542291 0.25717827
163 0.31995293 0.71289955
164 0.94358818 2.10244548
165 0.45462335 1.01296396
166 0.31962915 0.71217812
167 0.21999175 0.49017216
168 0.22389646 0.49887239
169 0.54689583 1.21855985
170 NA NA
171 NA NA
172 NA NA
173 1.09269710 2.43468086
174 0.19937519 0.44423560
175 0.17619793 0.39259345
176 0.11403186 0.25407881
177 1.33296418 2.97002928
178 NA NA
179 0.31522111 0.70235639
180 0.85108847 1.89634329
181 0.20165144 0.44930740
182 0.85403870 1.90291682
183 0.76065890 1.69485365
184 NA NA
185 NA NA
186 0.29549266 0.65839867
187 0.59384655 1.32317256
188 0.60364862 1.34501293
189 0.43074671 0.95976347
190 NA NA
191 0.77394815 1.72446395
192 0.32855167 0.73205874
193 1.13353341 2.52566984
194 0.49369519 1.10002144
195 0.08784377 0.19572812
196 0.22191202 0.49445079
197 0.29034238 0.64692314
198 0.26018454 0.57972728
199 0.23479685 0.52315998
200 NA NA
201 1.22553166 2.73065471
202 0.40880819 0.91088140
203 1.25787662 2.80272376
204 0.52558627 1.17107919
205 0.51753534 1.15314059# If I wanted to look at each country's score as an average all scores
SPI %>%
group_by(`Country`) %>%
dplyr::summarise(mean = mean(`Access-knowledge`))
# A tibble: 205 × 2
Country mean
<chr> <dbl>
1 Albania 89.8
2 Algeria 73.4
3 American Samoa NA
4 Andorra NA
5 Angola 47.8
6 Antigua and Barbuda NA
7 Argentina 84.6
8 Armenia 93.8
9 Australia 95.0
10 Austria 96.3
# … with 195 more rows# Access to Information & Communications
summarySE(SPI, measurevar="Info-comm", groupvars=c("Country"))
Country N Info-comm sd se
1 Albania 11 66.801818 9.827059 2.9629699
2 Algeria 11 45.510909 5.884117 1.7741279
3 American Samoa 11 NA NA NA
4 Andorra 11 NA NA NA
5 Angola 11 29.800000 7.587359 2.2876748
6 Antigua and Barbuda 11 NA NA NA
7 Argentina 11 71.663637 9.979380 3.0088962
8 Armenia 11 60.273636 14.826002 4.4702077
9 Australia 11 92.228182 2.770895 0.8354563
10 Austria 11 84.960909 6.621803 1.9965488
11 Azerbaijan 11 61.018182 11.843858 3.5710575
12 Bahamas, The 11 NA NA NA
13 Bahrain 11 74.641818 4.810397 1.4503892
14 Bangladesh 11 45.288182 14.467276 4.3620479
15 Barbados 11 70.760909 8.653914 2.6092533
16 Belarus 11 59.132727 12.680568 3.8233350
17 Belgium 11 83.478183 6.431906 1.9392927
18 Belize 11 NA NA NA
19 Benin 11 43.671818 6.061973 1.8277536
20 Bermuda 11 NA NA NA
21 Bhutan 11 52.334545 13.542376 4.0831799
22 Bolivia 11 56.540910 9.885729 2.9806595
23 Bosnia and Herzegovina 11 60.578181 10.743072 3.2391581
24 Botswana 11 54.880909 7.765091 2.3412632
25 Brazil 11 75.220909 8.044118 2.4253930
26 Brunei Darussalam 11 NA NA NA
27 Bulgaria 11 69.113636 10.209698 3.0783398
28 Burkina Faso 11 42.892728 14.778085 4.4557604
29 Burundi 11 17.472727 7.085940 2.1364911
30 Cabo Verde 11 58.617274 9.222828 2.7807873
31 Cambodia 11 40.030000 8.948485 2.6980697
32 Cameroon 11 36.806364 8.868500 2.6739533
33 Canada 11 85.517273 5.798995 1.7484628
34 Central African Republic 11 19.194546 4.433561 1.3367691
35 Chad 11 18.242727 3.567086 1.0755168
36 Chile 11 81.260910 8.572381 2.5846702
37 China 11 56.286363 13.471490 4.0618071
38 Colombia 11 76.465455 7.983108 2.4069977
39 Comoros 11 26.375454 4.994504 1.5058995
40 Congo, Democratic Republic of 11 18.617273 5.508771 1.6609571
41 Congo, Republic of 11 35.154545 3.009653 0.9074444
42 Cook Islands 11 NA NA NA
43 Costa Rica 11 71.380909 14.588409 4.3985708
44 Côte d'Ivoire 11 45.909090 8.816817 2.6583703
45 Croatia 11 74.899091 6.492537 1.9575734
46 Cuba 11 24.951818 13.154004 3.9660815
47 Cyprus 11 75.611817 9.658722 2.9122144
48 Czechia 11 74.647272 5.829893 1.7577788
49 Denmark 11 91.058181 5.706691 1.7206320
50 Djibouti 11 19.629091 12.241085 3.6908259
51 Dominica 11 NA NA NA
52 Dominican Republic 11 64.100909 8.464146 2.5520360
53 Ecuador 11 60.982727 9.645827 2.9083263
54 Egypt 11 54.494546 7.061709 2.1291853
55 El Salvador 11 61.411819 7.273598 2.1930723
56 Equatorial Guinea 11 22.260000 3.930687 1.1851467
57 Eritrea 11 4.879091 1.841676 0.5552861
58 Estonia 11 89.744547 4.200659 1.2665464
59 Eswatini 11 38.763637 9.155263 2.7604158
60 Ethiopia 11 24.318182 13.265591 3.9997263
61 Fiji 11 49.979091 12.238518 3.6900521
62 Finland 11 89.757274 5.584453 1.6837760
63 France 11 87.611818 6.135723 1.8499902
64 Gabon 11 51.201818 5.996060 1.8078802
65 Gambia, The 11 40.715455 10.806696 3.2583414
66 Georgia 11 65.191818 13.473306 4.0623547
67 Germany 11 88.414545 2.927639 0.8827164
68 Ghana 11 57.670000 12.825333 3.8669835
69 Greece 11 75.334546 8.175562 2.4650248
70 Greenland 11 NA NA NA
71 Grenada 11 NA NA NA
72 Guam 11 NA NA NA
73 Guatemala 11 58.405454 8.019098 2.4178491
74 Guinea 11 38.957273 12.334356 3.7189482
75 Guinea-Bissau 11 31.375455 4.738047 1.4285749
76 Guyana 11 47.650909 7.176544 2.1638095
77 Haiti 11 34.346364 8.283163 2.4974677
78 Honduras 11 51.797272 4.199007 1.2660483
79 Hong Kong 11 NA NA NA
80 Hungary 11 73.321818 3.580013 1.0794144
81 Iceland 11 83.173637 8.253979 2.4886683
82 India 11 51.775455 10.799029 3.2560296
83 Indonesia 11 56.974545 10.303296 3.1065608
84 Iran 11 46.862727 13.957534 4.2083550
85 Iraq 11 49.124545 12.617603 3.8043503
86 Ireland 11 82.962727 8.581341 2.5873716
87 Israel 11 80.309091 5.810737 1.7520031
88 Italy 11 78.037273 10.864564 3.2757893
89 Jamaica 11 60.538182 6.277933 1.8928681
90 Japan 11 89.801819 4.448747 1.3413478
91 Jordan 11 55.193636 7.822102 2.3584526
92 Kazakhstan 11 70.747273 7.818192 2.3572736
93 Kenya 11 49.105454 11.208553 3.3795060
94 Kiribati 11 NA NA NA
95 Korea, Democratic Republic of 11 3.374545 1.871397 0.5642475
96 Korea, Republic of 11 93.100000 3.565774 1.0751212
97 Kosovo 11 NA NA NA
98 Kuwait 11 71.987273 10.667591 3.2163996
99 Kyrgyzstan 11 60.403636 7.175585 2.1635203
100 Laos 11 28.204546 3.350407 1.0101857
101 Latvia 11 78.930909 6.904168 2.0816851
102 Lebanon 11 55.780000 7.573882 2.2836114
103 Lesotho 11 41.310000 10.418320 3.1412416
104 Liberia 11 34.433636 9.126371 2.7517044
105 Libya 11 46.887273 3.261626 0.9834172
106 Lithuania 11 81.530909 4.594324 1.3852407
107 Luxembourg 11 86.350001 7.821778 2.3583548
108 Madagascar 11 26.498182 6.272089 1.8911059
109 Malawi 11 26.956364 7.574918 2.2839238
110 Malaysia 11 72.862727 8.070103 2.4332276
111 Maldives 11 56.833636 7.575763 2.2841786
112 Mali 11 42.866364 8.066284 2.4320763
113 Malta 11 78.396364 7.863685 2.3709902
114 Marshall Islands 11 NA NA NA
115 Mauritania 11 44.614546 5.150500 1.5529341
116 Mauritius 11 65.926364 11.142408 3.3595625
117 Mexico 11 67.737272 11.323664 3.4142132
118 Micronesia 11 NA NA NA
119 Moldova 11 67.052727 15.061666 4.5412631
120 Monaco 11 NA NA NA
121 Mongolia 11 64.902728 7.186159 2.1667085
122 Montenegro 11 69.510000 10.246367 3.0893960
123 Morocco 11 67.232726 9.785489 2.9504360
124 Mozambique 11 34.440000 8.370687 2.5238571
125 Myanmar 11 28.559091 21.024274 6.3390570
126 Namibia 11 52.752727 8.580899 2.5872383
127 Nauru 11 NA NA NA
128 Nepal 11 48.735454 16.794719 5.0637984
129 Netherlands 11 94.563637 4.332968 1.3064389
130 New Zealand 11 90.642727 5.134834 1.5482106
131 Nicaragua 11 45.681818 6.710109 2.0231739
132 Niger 11 26.555454 5.207153 1.5700158
133 Nigeria 11 47.876364 10.948784 3.3011825
134 Niue 11 NA NA NA
135 Northern Mariana Islands 11 NA NA NA
136 Norway 11 91.384546 4.664872 1.4065118
137 Oman 11 65.825455 12.892709 3.8872981
138 Pakistan 11 42.015455 4.951360 1.4928912
139 Palau 11 NA NA NA
140 Panama 11 65.559091 8.565688 2.5826520
141 Papua New Guinea 11 26.931818 5.956438 1.7959337
142 Paraguay 11 63.798182 12.036507 3.6291433
143 Peru 11 70.490909 9.175049 2.7663814
144 Philippines 11 66.101818 11.069628 3.3376186
145 Poland 11 76.559999 7.407314 2.2333891
146 Portugal 11 78.170000 9.022171 2.7202869
147 Puerto Rico 11 NA NA NA
148 Qatar 11 71.520910 9.153474 2.7598761
149 Republic of North Macedonia 11 66.685456 11.342397 3.4198614
150 Romania 11 69.197273 10.304458 3.1069109
151 Russia 11 67.834546 10.880587 3.2806205
152 Rwanda 11 40.912727 14.916472 4.4974854
153 Samoa 11 NA NA NA
154 San Marino 11 NA NA NA
155 Sao Tome and Principe 11 42.016364 6.805073 2.0518068
156 Saudi Arabia 11 64.753637 11.551356 3.4828650
157 Senegal 11 52.845455 13.730655 4.1399484
158 Serbia 11 62.587273 10.560955 3.1842477
159 Seychelles 11 61.552728 8.272260 2.4941803
160 Sierra Leone 11 37.263637 13.472368 4.0620719
161 Singapore 11 80.037274 4.108035 1.2386191
162 Slovakia 11 78.022728 8.571181 2.5843083
163 Slovenia 11 78.244546 6.970668 2.1017354
164 Solomon Islands 11 34.830909 9.526480 2.8723419
165 Somalia 11 22.414545 6.245297 1.8830278
166 South Africa 11 64.605455 10.626680 3.2040646
167 South Sudan 11 11.370000 1.421506 0.4286003
168 Spain 11 86.133637 6.284016 1.8947021
169 Sri Lanka 11 54.420909 12.795304 3.8579295
170 St Kitts and Nevis 11 NA NA NA
171 St Lucia 11 NA NA NA
172 St Vincent and the Grenadines 11 NA NA NA
173 Sudan 11 33.746364 7.090185 2.1377712
174 Suriname 11 57.191818 4.896961 1.4764893
175 Sweden 11 89.920908 4.285497 1.2921261
176 Switzerland 11 83.044545 7.668331 2.3120888
177 Syria 11 36.005454 11.920020 3.5940211
178 Taiwan 11 NA NA NA
179 Tajikistan 11 38.946364 7.259409 2.1887940
180 Tanzania 11 39.924546 11.116013 3.3516040
181 Thailand 11 56.039091 10.065653 3.0349084
182 Timor-Leste 11 43.425455 14.621031 4.4084067
183 Togo 11 37.044546 10.374589 3.1280564
184 Tokelau 11 NA NA NA
185 Tonga 11 NA NA NA
186 Trinidad and Tobago 11 69.255454 9.542548 2.8771864
187 Tunisia 11 70.064545 9.854519 2.9712492
188 Turkey 11 60.338182 10.680389 3.2202585
189 Turkmenistan 11 33.300909 8.704043 2.6243678
190 Tuvalu 11 NA NA NA
191 Uganda 11 37.226364 9.503564 2.8654324
192 Ukraine 11 63.779090 11.097601 3.3460527
193 United Arab Emirates 11 75.191819 10.333852 3.1157735
194 United Kingdom 11 94.078182 2.974908 0.8969685
195 United States 11 89.124546 4.022251 1.2127543
196 Uruguay 11 78.143635 11.222107 3.3835926
197 Uzbekistan 11 47.503636 12.888372 3.8859904
198 Vanuatu 11 42.941818 9.029949 2.7226319
199 Vietnam 11 57.615456 10.465515 3.1554716
200 Virgin Islands (US) 11 NA NA NA
201 West Bank and Gaza 11 54.360000 8.537106 2.5740344
202 World 11 60.173637 9.929886 2.9939733
203 Yemen 11 27.696364 5.351148 1.6134318
204 Zambia 11 35.218182 8.808050 2.6557269
205 Zimbabwe 11 41.566364 12.362504 3.7274353
ci
1 6.601908
2 3.953003
3 NA
4 NA
5 5.097257
6 NA
7 6.704238
8 9.960244
9 1.861513
10 4.448588
11 7.956812
12 NA
13 3.231669
14 9.719248
15 5.813779
16 8.518921
17 4.321013
18 NA
19 4.072489
20 NA
21 9.097892
22 6.641323
23 7.217294
24 5.216659
25 5.404112
26 NA
27 6.858969
28 9.928053
29 4.760399
30 6.195980
31 6.011674
32 5.957939
33 3.895818
34 2.978507
35 2.396401
36 5.759004
37 9.050270
38 5.363125
39 3.355353
40 3.700843
41 2.021912
42 NA
43 9.800627
44 5.923218
45 4.361745
46 8.836980
47 6.488818
48 3.916575
49 3.833807
50 8.223673
51 NA
52 5.686291
53 6.480155
54 4.744121
55 4.886470
56 2.640671
57 1.237254
58 2.822041
59 6.150590
60 8.911946
61 8.221949
62 3.751687
63 4.122035
64 4.028208
65 7.260037
66 9.051490
67 1.966815
68 8.616176
69 5.492417
70 NA
71 NA
72 NA
73 5.387304
74 8.286333
75 3.183063
76 4.821268
77 5.564705
78 2.820931
79 NA
80 2.405085
81 5.545099
82 7.254886
83 6.921849
84 9.376799
85 8.476621
86 5.765023
87 3.903706
88 7.298913
89 4.217573
90 2.988709
91 5.254960
92 5.252333
93 7.530009
94 NA
95 1.257222
96 2.395519
97 NA
98 7.166585
99 4.820624
100 2.250834
101 4.638283
102 5.088203
103 6.999122
104 6.131179
105 2.191190
106 3.086509
107 5.254742
108 4.213647
109 5.088899
110 5.421569
111 5.089467
112 5.419004
113 5.282895
114 NA
115 3.460153
116 7.485572
117 7.607341
118 NA
119 10.118565
120 NA
121 4.827727
122 6.883603
123 6.573981
124 5.623504
125 14.124299
126 5.764726
127 NA
128 11.282846
129 2.910927
130 3.449628
131 4.507912
132 3.498213
133 7.355493
134 NA
135 NA
136 3.133903
137 8.661440
138 3.326369
139 NA
140 5.754507
141 4.001590
142 8.086235
143 6.163882
144 7.436678
145 4.976301
146 6.061177
147 NA
148 6.149387
149 7.619926
150 6.922629
151 7.309678
152 10.021022
153 NA
154 NA
155 4.571711
156 7.760307
157 9.224380
158 7.094946
159 5.557380
160 9.050860
161 2.759815
162 5.758198
163 4.682958
164 6.399977
165 4.195647
166 7.139101
167 0.954981
168 4.221659
169 8.596003
170 NA
171 NA
172 NA
173 4.763251
174 3.289823
175 2.879036
176 5.151655
177 8.007978
178 NA
179 4.876937
180 7.467839
181 6.762197
182 9.822542
183 6.969744
184 NA
185 NA
186 6.410771
187 6.620356
188 7.175183
189 5.847456
190 NA
191 6.384581
192 7.455470
193 6.942376
194 1.998570
195 2.702185
196 7.539114
197 8.658526
198 6.066402
199 7.030829
200 NA
201 5.735306
202 6.670988
203 3.594950
204 5.917328
205 8.305243# Looking at the average information and communications score for each country
SPI %>%
group_by(`Country`) %>%
dplyr::summarise(mean = mean(`Info-comm`))
# A tibble: 205 × 2
Country mean
<chr> <dbl>
1 Albania 66.8
2 Algeria 45.5
3 American Samoa NA
4 Andorra NA
5 Angola 29.8
6 Antigua and Barbuda NA
7 Argentina 71.7
8 Armenia 60.3
9 Australia 92.2
10 Austria 85.0
# … with 195 more rows Country N Health sd se
1 Albania 11 72.41636 0.8142137 0.24549467
2 Algeria 11 68.70818 1.5406599 0.46452643
3 American Samoa 11 NA NA NA
4 Andorra 11 NA NA NA
5 Angola 11 41.53364 2.1846344 0.65869206
6 Antigua and Barbuda 11 NA NA NA
7 Argentina 11 68.17727 0.5936504 0.17899234
8 Armenia 11 65.99636 1.4739623 0.44441635
9 Australia 11 86.54091 0.5312514 0.16017832
10 Austria 11 85.67909 1.0793832 0.32544627
11 Azerbaijan 11 45.59182 1.4763462 0.44513512
12 Bahamas, The 11 NA NA NA
13 Bahrain 11 71.06182 1.7754480 0.53531771
14 Bangladesh 11 49.84182 2.5689250 0.77456004
15 Barbados 11 72.95909 0.2582426 0.07786306
16 Belarus 11 64.80636 3.1760180 0.95760547
17 Belgium 11 84.93545 1.1367521 0.34274364
18 Belize 11 NA NA NA
19 Benin 11 51.25182 1.1723549 0.35347831
20 Bermuda 11 NA NA NA
21 Bhutan 11 63.99818 1.6496410 0.49738548
22 Bolivia 11 54.30818 0.7276231 0.21938662
23 Bosnia and Herzegovina 11 65.65636 0.6153601 0.18553804
24 Botswana 11 55.82455 1.3693094 0.41286231
25 Brazil 11 65.44636 0.7574853 0.22839041
26 Brunei Darussalam 11 NA NA NA
27 Bulgaria 11 61.02000 0.7438420 0.22427679
28 Burkina Faso 11 44.79091 0.8983922 0.27087544
29 Burundi 11 42.21182 0.5840175 0.17608790
30 Cabo Verde 11 68.50000 1.7136344 0.51668021
31 Cambodia 11 47.52909 0.9846773 0.29689136
32 Cameroon 11 46.17818 2.8022057 0.84489681
33 Canada 11 86.92727 0.5277136 0.15911165
34 Central African Republic 11 25.07818 1.0608661 0.31986316
35 Chad 11 39.59000 1.4938341 0.45040791
36 Chile 11 74.42818 1.1120690 0.33530141
37 China 11 63.56636 1.4739218 0.44440413
38 Colombia 11 71.90273 1.0398952 0.31354020
39 Comoros 11 48.90455 2.7327874 0.82396640
40 Congo, Democratic Republic of 11 40.89636 1.7315667 0.52208701
41 Congo, Republic of 11 41.02909 1.9886149 0.59958997
42 Cook Islands 11 NA NA NA
43 Costa Rica 11 81.37727 0.4902886 0.14782758
44 Côte d'Ivoire 11 43.46273 2.4742355 0.74601009
45 Croatia 11 75.34455 1.1228125 0.33854070
46 Cuba 11 74.52909 0.8355425 0.25192555
47 Cyprus 11 82.72545 1.4754612 0.44486830
48 Czechia 11 78.89364 1.4167502 0.42716625
49 Denmark 11 83.21273 1.4637972 0.44135147
50 Djibouti 11 45.56000 1.1069595 0.33376086
51 Dominica 11 NA NA NA
52 Dominican Republic 11 57.36091 1.0562718 0.31847793
53 Ecuador 11 68.85545 0.6107924 0.18416084
54 Egypt 11 43.44364 1.2357845 0.37260306
55 El Salvador 11 63.39818 1.0568995 0.31866719
56 Equatorial Guinea 11 50.32455 0.9527160 0.28725468
57 Eritrea 11 42.24091 1.6754667 0.50517221
58 Estonia 11 75.88091 1.9422180 0.58560075
59 Eswatini 11 36.35273 4.6378273 1.39835754
60 Ethiopia 11 47.55182 3.7836802 1.14082251
61 Fiji 11 40.16455 2.1783446 0.65679560
62 Finland 11 85.01091 0.8763942 0.26424281
63 France 11 87.74091 0.6893687 0.20785248
64 Gabon 11 51.60091 2.7182255 0.81957581
65 Gambia, The 11 46.02545 0.9529363 0.28732112
66 Georgia 11 60.83091 1.6549893 0.49899806
67 Germany 11 83.60818 0.6812308 0.20539880
68 Ghana 11 51.00636 1.8573065 0.55999897
69 Greece 11 82.55727 0.4518638 0.13624207
70 Greenland 11 NA NA NA
71 Grenada 11 NA NA NA
72 Guam 11 NA NA NA
73 Guatemala 11 58.46455 0.5679143 0.17123260
74 Guinea 11 36.08364 0.6025321 0.18167027
75 Guinea-Bissau 11 33.11636 1.2108778 0.36509339
76 Guyana 11 49.16545 1.5537657 0.46847799
77 Haiti 11 34.42636 2.8034382 0.84526842
78 Honduras 11 52.05273 1.3182874 0.39747861
79 Hong Kong 11 NA NA NA
80 Hungary 11 66.52455 0.9731739 0.29342297
81 Iceland 11 89.57909 0.9309708 0.28069825
82 India 11 47.87273 1.0427282 0.31439440
83 Indonesia 11 52.14909 1.8978379 0.57221965
84 Iran 11 71.49909 0.7750036 0.23367238
85 Iraq 11 59.13909 1.5391647 0.46407561
86 Ireland 11 83.04909 1.0022607 0.30219297
87 Israel 11 85.83455 0.6019031 0.18148061
88 Italy 11 87.68818 1.0721459 0.32326415
89 Jamaica 11 66.30818 0.7513297 0.22653442
90 Japan 11 90.72000 1.1219539 0.33828182
91 Jordan 11 71.81273 1.7418801 0.52519662
92 Kazakhstan 11 56.57636 3.3656030 1.01476747
93 Kenya 11 51.00273 1.1622916 0.35044411
94 Kiribati 11 NA NA NA
95 Korea, Democratic Republic of 11 52.54000 1.2598575 0.37986134
96 Korea, Republic of 11 87.28364 1.7955287 0.54137228
97 Kosovo 11 NA NA NA
98 Kuwait 11 82.84000 1.9303889 0.58203415
99 Kyrgyzstan 11 55.94636 2.8960429 0.87318980
100 Laos 11 42.45818 2.4098831 0.72660709
101 Latvia 11 67.25909 1.9717576 0.59450728
102 Lebanon 11 66.57000 0.9564410 0.28837782
103 Lesotho 11 35.78273 1.9057965 0.57461927
104 Liberia 11 45.46818 1.2255354 0.36951283
105 Libya 11 60.39727 2.3375373 0.70479402
106 Lithuania 11 69.94364 1.2432090 0.37484162
107 Luxembourg 11 86.91000 1.3990704 0.42183560
108 Madagascar 11 36.26000 1.1851159 0.35732590
109 Malawi 11 45.03182 1.5508184 0.46758933
110 Malaysia 11 66.85364 0.9108592 0.27463439
111 Maldives 11 69.54636 1.0976182 0.33094432
112 Mali 11 45.01909 0.4433392 0.13367179
113 Malta 11 85.49636 1.2390033 0.37357356
114 Marshall Islands 11 NA NA NA
115 Mauritania 11 50.96000 1.9081667 0.57533392
116 Mauritius 11 68.59909 0.9883474 0.29799795
117 Mexico 11 64.37455 0.4625666 0.13946906
118 Micronesia 11 NA NA NA
119 Moldova 11 58.99818 2.0150181 0.60755081
120 Monaco 11 NA NA NA
121 Mongolia 11 45.63182 2.6536905 0.80011779
122 Montenegro 11 67.38273 0.5059076 0.15253687
123 Morocco 11 53.64546 1.1146870 0.33609076
124 Mozambique 11 37.46454 1.3759825 0.41487433
125 Myanmar 11 45.09273 3.0484653 0.91914688
126 Namibia 11 51.65455 1.7752088 0.53524558
127 Nauru 11 NA NA NA
128 Nepal 11 49.25636 0.8205159 0.24739486
129 Netherlands 11 86.13455 0.8040695 0.24243607
130 New Zealand 11 85.04182 0.9373654 0.28262630
131 Nicaragua 11 65.60545 1.6225856 0.48922798
132 Niger 11 45.37364 0.4313533 0.13005793
133 Nigeria 11 50.25818 0.6136742 0.18502973
134 Niue 11 NA NA NA
135 Northern Mariana Islands 11 NA NA NA
136 Norway 11 87.84454 1.2736285 0.38401345
137 Oman 11 64.76273 2.6218624 0.79052127
138 Pakistan 11 38.43818 1.6540606 0.49871802
139 Palau 11 NA NA NA
140 Panama 11 76.34545 1.0397437 0.31349454
141 Papua New Guinea 11 18.00545 1.9339927 0.58312075
142 Paraguay 11 60.31000 0.6806179 0.20521403
143 Peru 11 70.41545 2.0701224 0.62416540
144 Philippines 11 48.74818 0.6003133 0.18100127
145 Poland 11 73.07909 1.1696703 0.35266885
146 Portugal 11 82.86364 1.0181779 0.30699219
147 Puerto Rico 11 NA NA NA
148 Qatar 11 72.62545 2.0540768 0.61932745
149 Republic of North Macedonia 11 63.78636 0.6364006 0.19188199
150 Romania 11 65.50182 1.1595841 0.34962775
151 Russia 11 60.87091 3.1976931 0.96414075
152 Rwanda 11 56.85546 1.4415367 0.43463967
153 Samoa 11 NA NA NA
154 San Marino 11 NA NA NA
155 Sao Tome and Principe 11 52.98364 0.8143865 0.24554677
156 Saudi Arabia 11 67.84273 2.8285938 0.85285313
157 Senegal 11 51.45000 1.1284235 0.34023247
158 Serbia 11 64.15545 1.5148748 0.45675193
159 Seychelles 11 65.27818 0.7051629 0.21261462
160 Sierra Leone 11 42.86182 1.7345246 0.52297885
161 Singapore 11 87.96364 1.7215820 0.51907651
162 Slovakia 11 72.09000 1.5254622 0.45994415
163 Slovenia 11 81.77818 1.0507691 0.31681880
164 Solomon Islands 11 29.26727 1.1774898 0.35502654
165 Somalia 11 27.85182 1.0608093 0.31984605
166 South Africa 11 51.80455 2.1048677 0.63464150
167 South Sudan 11 36.09727 0.8600359 0.25931058
168 Spain 11 86.78182 0.9851376 0.29703016
169 Sri Lanka 11 70.27182 1.8734825 0.56487624
170 St Kitts and Nevis 11 NA NA NA
171 St Lucia 11 NA NA NA
172 St Vincent and the Grenadines 11 NA NA NA
173 Sudan 11 45.65909 2.3891858 0.72036662
174 Suriname 11 61.26818 0.7198866 0.21705398
175 Sweden 11 86.91636 0.6018683 0.18147012
176 Switzerland 11 90.31909 0.9558707 0.28820586
177 Syria 11 53.71636 2.4169497 0.72873775
178 Taiwan 11 82.54818 0.8998864 0.27132597
179 Tajikistan 11 46.47636 0.4441003 0.13390126
180 Tanzania 11 53.43182 1.5950041 0.48091182
181 Thailand 11 74.35091 0.6447556 0.19440114
182 Timor-Leste 11 48.02000 0.8279372 0.24963247
183 Togo 11 45.98545 2.3045454 0.69484658
184 Tokelau 11 NA NA NA
185 Tonga 11 NA NA NA
186 Trinidad and Tobago 11 66.60455 0.6300526 0.18996801
187 Tunisia 11 68.47818 0.7033182 0.21205841
188 Turkey 11 70.93273 0.8126761 0.24503106
189 Turkmenistan 11 49.68364 0.7937418 0.23932217
190 Tuvalu 11 NA NA NA
191 Uganda 11 47.19364 1.3662086 0.41192738
192 Ukraine 11 59.38636 1.1266877 0.33970911
193 United Arab Emirates 11 57.10273 2.9853851 0.90012749
194 United Kingdom 11 84.27364 0.5370527 0.16192748
195 United States 11 75.82273 0.6660646 0.20082602
196 Uruguay 11 72.87273 1.0850269 0.32714791
197 Uzbekistan 11 45.67545 1.4241446 0.42939574
198 Vanuatu 11 35.96545 1.2426046 0.37465939
199 Vietnam 11 62.21545 1.3620901 0.41068563
200 Virgin Islands (US) 11 NA NA NA
201 West Bank and Gaza 11 62.64909 2.5893104 0.78070646
202 World 11 59.00182 0.9149187 0.27585836
203 Yemen 11 41.32182 1.1505717 0.34691041
204 Zambia 11 44.62455 1.3143693 0.39629725
205 Zimbabwe 11 36.73636 2.8026393 0.84502755
ci
1 0.5469962
2 1.0350294
3 NA
4 NA
5 1.4676574
6 NA
7 0.3988198
8 0.9902213
9 0.3568995
10 0.7251395
11 0.9918229
12 NA
13 1.1927622
14 1.7258273
15 0.1734897
16 2.1336780
17 0.7636804
18 NA
19 0.7875988
20 NA
21 1.1082439
22 0.4888238
23 0.4134045
24 0.9199146
25 0.5088856
26 NA
27 0.4997198
28 0.6035481
29 0.3923483
30 1.1512352
31 0.6615152
32 1.8825474
33 0.3545229
34 0.7126995
35 1.0035714
36 0.7470981
37 0.9901941
38 0.6986111
39 1.8359116
40 1.1632823
41 1.3359697
42 NA
43 0.3293804
44 1.6622141
45 0.7543157
46 0.5613251
47 0.9912283
48 0.9517857
49 0.9833924
50 0.7436655
51 NA
52 0.7096130
53 0.4103359
54 0.8302113
55 0.7100347
56 0.6400433
57 1.1255938
58 1.3047998
59 3.1157348
60 2.5419109
61 1.4634318
62 0.5887697
63 0.4631242
64 1.8261287
65 0.6401913
66 1.1118370
67 0.4576570
68 1.2477555
69 0.3035663
70 NA
71 NA
72 NA
73 0.3815300
74 0.4047866
75 0.8134788
76 1.0438340
77 1.8833754
78 0.8856375
79 NA
80 0.6537871
81 0.6254347
82 0.7005144
83 1.2749848
84 0.5206545
85 1.0340249
86 0.6733279
87 0.4043640
88 0.7202774
89 0.5047501
90 0.7537389
91 1.1702110
92 2.2610428
93 0.7808381
94 NA
95 0.8463838
96 1.2062526
97 NA
98 1.2968529
99 1.9455881
100 1.6189815
101 1.3246448
102 0.6425458
103 1.2803315
104 0.8233259
105 1.5703789
106 0.8351992
107 0.9399083
108 0.7961717
109 1.0418540
110 0.6119236
111 0.7373899
112 0.2978393
113 0.8323738
114 NA
115 1.2819239
116 0.6639808
117 0.3107564
118 NA
119 1.3537076
120 NA
121 1.7827735
122 0.3398733
123 0.7488569
124 0.9243976
125 2.0479869
126 1.1926015
127 NA
128 0.5512301
129 0.5401812
130 0.6297306
131 1.0900679
132 0.2897871
133 0.4122719
134 NA
135 NA
136 0.8556353
137 1.7613911
138 1.1112130
139 NA
140 0.6985094
141 1.2992740
142 0.4572454
143 1.3907272
144 0.4032960
145 0.7857952
146 0.6840212
147 NA
148 1.3799475
149 0.4275397
150 0.7790192
151 2.1482395
152 0.9684375
153 NA
154 NA
155 0.5471123
156 1.9002752
157 0.7580852
158 1.0177067
159 0.4737349
160 1.1652695
161 1.1565745
162 1.0248194
163 0.7059163
164 0.7910484
165 0.7126614
166 1.4140694
167 0.5777800
168 0.6618244
169 1.2586227
170 NA
171 NA
172 NA
173 1.6050768
174 0.4836264
175 0.4043406
176 0.6421627
177 1.6237289
178 0.6045519
179 0.2983506
180 1.0715383
181 0.4331527
182 0.5562158
183 1.5482147
184 NA
185 NA
186 0.4232751
187 0.4724956
188 0.5459632
189 0.5332430
190 NA
191 0.9178314
192 0.7569191
193 2.0056090
194 0.3607969
195 0.4474683
196 0.7289310
197 0.9567533
198 0.8347931
199 0.9150646
200 NA
201 1.7395224
202 0.6146507
203 0.7729646
204 0.8830053
205 1.8828387# Looking at the average health and wellness score of all years for each country
SPI %>%
group_by(`Country`) %>%
dplyr::summarise(mean = mean(`Health`))
# A tibble: 205 × 2
Country mean
<chr> <dbl>
1 Albania 72.4
2 Algeria 68.7
3 American Samoa NA
4 Andorra NA
5 Angola 41.5
6 Antigua and Barbuda NA
7 Argentina 68.2
8 Armenia 66.0
9 Australia 86.5
10 Austria 85.7
# … with 195 more rows Country N Environment sd se
1 Albania 11 70.98000 0.9247067 0.27880957
2 Algeria 11 51.70000 0.5673095 0.17105025
3 American Samoa 11 NA NA NA
4 Andorra 11 NA NA NA
5 Angola 11 62.90182 0.4064680 0.12255471
6 Antigua and Barbuda 11 NA NA NA
7 Argentina 11 78.00091 0.6484503 0.19551514
8 Armenia 11 58.31636 1.8832431 0.56781917
9 Australia 11 85.14273 1.3274577 0.40024356
10 Austria 11 83.37091 1.2196992 0.36775315
11 Azerbaijan 11 55.22000 0.9949376 0.29998498
12 Bahamas, The 11 69.18273 1.0073543 0.30372874
13 Bahrain 11 43.89545 2.9879138 0.90088991
14 Bangladesh 11 44.91636 1.4462449 0.43605925
15 Barbados 11 73.84818 0.8001219 0.24124582
16 Belarus 11 71.28546 2.9983788 0.90404523
17 Belgium 11 81.63364 1.4309184 0.43143813
18 Belize 11 73.32636 0.9000263 0.27136815
19 Benin 11 65.98091 1.2628417 0.38076109
20 Bermuda 11 NA NA NA
21 Bhutan 11 65.62000 0.6546308 0.19737862
22 Bolivia 11 68.53364 0.9980406 0.30092056
23 Bosnia and Herzegovina 11 55.35909 1.8757322 0.56555454
24 Botswana 11 63.50000 1.0069949 0.30362039
25 Brazil 11 77.66364 1.4165254 0.42709849
26 Brunei Darussalam 11 NA NA NA
27 Bulgaria 11 67.27273 1.7568618 0.52971378
28 Burkina Faso 11 66.16364 1.3115047 0.39543356
29 Burundi 11 63.80636 0.4963727 0.14966200
30 Cabo Verde 11 67.38636 3.7135187 1.11966802
31 Cambodia 11 69.04546 0.9804943 0.29563017
32 Cameroon 11 47.68455 2.1171893 0.63835658
33 Canada 11 91.92182 0.6466658 0.19497708
34 Central African Republic 11 58.68364 1.0863818 0.32755645
35 Chad 11 57.92545 1.6861515 0.50839381
36 Chile 11 78.33364 1.2372896 0.37305684
37 China 11 38.22273 3.4039150 1.02631900
38 Colombia 11 72.70727 1.8939331 0.57104233
39 Comoros 11 72.40091 0.3377705 0.10184163
40 Congo, Democratic Republic of 11 64.68818 0.6939430 0.20923169
41 Congo, Republic of 11 59.91364 1.3698188 0.41301592
42 Cook Islands 11 NA NA NA
43 Costa Rica 11 76.50818 0.7549422 0.22762365
44 Côte d'Ivoire 11 69.15636 0.8366142 0.25224866
45 Croatia 11 74.85818 6.2155996 1.87407379
46 Cuba 11 65.48273 1.8400383 0.55479241
47 Cyprus 11 74.89455 1.9953614 0.60162410
48 Czechia 11 79.83454 1.7518514 0.52820308
49 Denmark 11 88.95727 1.1742404 0.35404682
50 Djibouti 11 49.78636 1.8204850 0.54889687
51 Dominica 11 NA NA NA
52 Dominican Republic 11 68.37636 0.5909192 0.17816883
53 Ecuador 11 71.93182 1.6308457 0.49171847
54 Egypt 11 24.03909 1.5283878 0.46082625
55 El Salvador 11 58.84182 0.9687805 0.29209832
56 Equatorial Guinea 11 54.03182 2.0900618 0.63017735
57 Eritrea 11 56.33455 0.7702128 0.23222790
58 Estonia 11 89.60545 1.0791976 0.32539032
59 Eswatini 11 62.97727 0.8922451 0.26902201
60 Ethiopia 11 65.83546 0.3504377 0.10566095
61 Fiji 11 69.77909 0.3793264 0.11437122
62 Finland 11 94.43455 0.6617911 0.19953754
63 France 11 86.33364 1.2430303 0.37478774
64 Gabon 11 59.49182 0.4371001 0.13179063
65 Gambia, The 11 60.12818 1.4316830 0.43166865
66 Georgia 11 66.74364 1.3517640 0.40757219
67 Germany 11 86.74091 1.0207672 0.30777290
68 Ghana 11 64.97091 1.7389561 0.52431500
69 Greece 11 78.04273 1.5640348 0.47157424
70 Greenland 11 NA NA NA
71 Grenada 11 NA NA NA
72 Guam 11 NA NA NA
73 Guatemala 11 60.75000 1.1499746 0.34673037
74 Guinea 11 66.05000 0.6900721 0.20806455
75 Guinea-Bissau 11 62.46909 0.7790307 0.23488660
76 Guyana 11 54.65818 1.2887659 0.38857753
77 Haiti 11 57.07909 1.0774546 0.32486480
78 Honduras 11 62.54182 1.1270208 0.33980954
79 Hong Kong 11 NA NA NA
80 Hungary 11 77.87273 1.5716621 0.47387396
81 Iceland 11 89.81545 0.8959965 0.27015310
82 India 11 35.46364 0.6281448 0.18939279
83 Indonesia 11 64.66273 0.5770108 0.17397532
84 Iran 11 52.97091 0.9157562 0.27611089
85 Iraq 11 33.53636 3.6047257 1.08686569
86 Ireland 11 86.65000 1.1058838 0.33343651
87 Israel 11 80.88909 1.5088172 0.45492552
88 Italy 11 82.22091 1.2148938 0.36630426
89 Jamaica 11 73.49727 0.5988687 0.18056572
90 Japan 11 86.61364 0.8327463 0.25108247
91 Jordan 11 56.15364 1.7705948 0.53385443
92 Kazakhstan 11 66.54000 1.5714580 0.47381240
93 Kenya 11 70.55636 0.5193897 0.15660189
94 Kiribati 11 NA NA NA
95 Korea, Democratic Republic of 11 58.63364 0.9456557 0.28512593
96 Korea, Republic of 11 78.70909 1.4468350 0.43623717
97 Kosovo 11 NA NA NA
98 Kuwait 11 58.03909 2.4368231 0.73472982
99 Kyrgyzstan 11 59.75545 1.3916702 0.41960436
100 Laos 11 67.39909 1.1763119 0.35467137
101 Latvia 11 81.72273 2.3621132 0.71220394
102 Lebanon 11 52.77455 1.2472157 0.37604967
103 Lesotho 11 50.24455 0.9795649 0.29534993
104 Liberia 11 67.28000 0.5783946 0.17439253
105 Libya 11 55.98364 1.0747958 0.32406313
106 Lithuania 11 84.20545 1.9199445 0.57888506
107 Luxembourg 11 86.14818 1.5160715 0.45711277
108 Madagascar 11 64.59182 0.2863496 0.08633767
109 Malawi 11 71.44636 0.6474909 0.19522586
110 Malaysia 11 71.22000 1.2728547 0.38378013
111 Maldives 11 77.90636 1.3429912 0.40492708
112 Mali 11 65.42909 0.7724691 0.23290818
113 Malta 11 74.05091 1.8523353 0.55850012
114 Marshall Islands 11 NA NA NA
115 Mauritania 11 50.85182 1.3662052 0.41192637
116 Mauritius 11 76.28636 0.9190340 0.27709916
117 Mexico 11 65.42818 0.9840911 0.29671463
118 Micronesia 11 NA NA NA
119 Moldova 11 60.16182 2.4102072 0.72670480
120 Monaco 11 NA NA NA
121 Mongolia 11 53.76273 0.8687471 0.26193711
122 Montenegro 11 57.97273 1.3771640 0.41523058
123 Morocco 11 54.90000 3.8637673 1.16496967
124 Mozambique 11 67.96000 0.4652523 0.14027884
125 Myanmar 11 58.60727 1.6542974 0.49878945
126 Namibia 11 67.11727 0.3347861 0.10094180
127 Nauru 11 NA NA NA
128 Nepal 11 40.56364 1.4586999 0.43981456
129 Netherlands 11 86.29454 1.3136088 0.39606795
130 New Zealand 11 85.16546 0.7717184 0.23268184
131 Nicaragua 11 69.07000 0.9867730 0.29752324
132 Niger 11 54.12636 3.7763483 1.13861185
133 Nigeria 11 58.75182 3.2362719 0.97577271
134 Niue 11 NA NA NA
135 Northern Mariana Islands 11 NA NA NA
136 Norway 11 88.08455 1.1030620 0.33258572
137 Oman 11 39.35182 1.5364886 0.46326875
138 Pakistan 11 43.99364 0.4158428 0.12538131
139 Palau 11 NA NA NA
140 Panama 11 76.88000 0.9776402 0.29476961
141 Papua New Guinea 11 70.55818 0.5889457 0.17757380
142 Paraguay 11 76.66000 0.7504412 0.22626655
143 Peru 11 72.20636 1.8094268 0.54556271
144 Philippines 11 70.13727 0.8518938 0.25685563
145 Poland 11 74.94091 2.1366013 0.64420954
146 Portugal 11 82.52364 1.3385246 0.40358034
147 Puerto Rico 11 NA NA NA
148 Qatar 11 25.75182 1.8355591 0.55344190
149 Republic of North Macedonia 11 56.69455 2.3043673 0.69479289
150 Romania 11 73.36909 1.8476393 0.55708422
151 Russia 11 78.11909 2.6016941 0.78444029
152 Rwanda 11 64.70091 0.3859655 0.11637297
153 Samoa 11 NA NA NA
154 San Marino 11 NA NA NA
155 Sao Tome and Principe 11 65.20364 1.1739437 0.35395735
156 Saudi Arabia 11 32.66182 2.0745354 0.62549595
157 Senegal 11 65.92818 1.0865528 0.32760801
158 Serbia 11 63.94909 2.4725744 0.74550922
159 Seychelles 11 75.61182 0.5796524 0.17477178
160 Sierra Leone 11 69.22545 0.6181970 0.18639340
161 Singapore 11 80.79909 0.9323460 0.28111288
162 Slovakia 11 76.47636 1.9929592 0.60089981
163 Slovenia 11 84.63727 1.2006668 0.36201466
164 Solomon Islands 11 58.06455 0.1821737 0.05492743
165 Somalia 11 65.25636 0.2071838 0.06246826
166 South Africa 11 65.54727 1.7032677 0.51355455
167 South Sudan 11 63.10455 0.4822309 0.14539808
168 Spain 11 85.65091 0.8902309 0.26841470
169 Sri Lanka 11 74.68364 3.6528000 1.10136064
170 St Kitts and Nevis 11 NA NA NA
171 St Lucia 11 NA NA NA
172 St Vincent and the Grenadines 11 NA NA NA
173 Sudan 11 41.90000 2.0920473 0.63077599
174 Suriname 11 66.62273 0.7944203 0.23952672
175 Sweden 11 92.42636 0.6375013 0.19221386
176 Switzerland 11 88.78546 1.0134440 0.30556486
177 Syria 11 43.71455 0.6521862 0.19664154
178 Taiwan 11 77.42909 1.2461182 0.37571879
179 Tajikistan 11 41.40727 1.3352013 0.40257835
180 Tanzania 11 69.47364 0.5272054 0.15895839
181 Thailand 11 78.32364 1.5420001 0.46493054
182 Timor-Leste 11 72.00000 0.2694074 0.08122937
183 Togo 11 65.03182 1.2416990 0.37438632
184 Tokelau 11 NA NA NA
185 Tonga 11 NA NA NA
186 Trinidad and Tobago 11 73.74182 0.9336028 0.28149184
187 Tunisia 11 54.88818 1.0848764 0.32710254
188 Turkey 11 52.59545 0.9566651 0.28844539
189 Turkmenistan 11 57.42818 0.9503032 0.28652720
190 Tuvalu 11 NA NA NA
191 Uganda 11 64.90273 0.5909505 0.17817828
192 Ukraine 11 71.12364 1.8448653 0.55624783
193 United Arab Emirates 11 49.36818 7.2746333 2.19338446
194 United Kingdom 11 88.57000 0.9444780 0.28477084
195 United States 11 84.57455 0.9122520 0.27505433
196 Uruguay 11 73.00818 1.2026041 0.36259879
197 Uzbekistan 11 34.23000 1.8336962 0.55288020
198 Vanuatu 11 65.93455 0.2792624 0.08420079
199 Vietnam 11 62.98545 2.5073705 0.75600065
200 Virgin Islands (US) 11 NA NA NA
201 West Bank and Gaza 11 51.95545 1.0215515 0.30800937
202 World 11 54.00818 1.0074603 0.30376070
203 Yemen 11 40.24454 1.6980181 0.51197173
204 Zambia 11 69.22818 0.3791516 0.11431850
205 Zimbabwe 11 69.22545 0.4736733 0.14281787
ci
1 0.6212264
2 0.3811237
3 NA
4 NA
5 0.2730689
6 NA
7 0.4356349
8 1.2651799
9 0.8917982
10 0.8194051
11 0.6684082
12 0.6767498
13 2.0073078
14 0.9716006
15 0.5375292
16 2.0143383
17 0.9613041
18 0.6046459
19 0.8483886
20 NA
21 0.4397870
22 0.6704928
23 1.2601340
24 0.6765084
25 0.9516347
26 NA
27 1.1802758
28 0.8810809
29 0.3334677
30 2.4947758
31 0.6587051
32 1.4223471
33 0.4344360
34 0.7298412
35 1.1327720
36 0.8312224
37 2.2867812
38 1.2723616
39 0.2269173
40 0.4661973
41 0.9202568
42 NA
43 0.5071771
44 0.5620450
45 4.1756966
46 1.2361545
47 1.3405020
48 1.1769098
49 0.7888655
50 1.2230184
51 NA
52 0.3969849
53 1.0956170
54 1.0267849
55 0.6508356
56 1.4041226
57 0.5174360
58 0.7250148
59 0.5994184
60 0.2354273
61 0.2548350
62 0.4445973
63 0.8350791
64 0.2936478
65 0.9618177
66 0.9081274
67 0.6857608
68 1.1682466
69 1.0507329
70 NA
71 NA
72 NA
73 0.7725634
74 0.4635967
75 0.5233600
76 0.8658047
77 0.7238439
78 0.7571428
79 NA
80 1.0558570
81 0.6019386
82 0.4219934
83 0.3876412
84 0.6152134
85 2.4216877
86 0.7429428
87 1.0136372
88 0.8161768
89 0.4023255
90 0.5594466
91 1.1895018
92 1.0557198
93 0.3489307
94 NA
95 0.6353002
96 0.9719970
97 NA
98 1.6370801
99 0.9349368
100 0.7902571
101 1.5868893
102 0.8378909
103 0.6580807
104 0.3885708
105 0.7220577
106 1.2898363
107 1.0185107
108 0.1923723
109 0.4349903
110 0.8551154
111 0.9022337
112 0.5189518
113 1.2444158
114 NA
115 0.9178291
116 0.6174154
117 0.6611214
118 NA
119 1.6191992
120 NA
121 0.5836323
122 0.9251914
123 2.5957142
124 0.3125607
125 1.1113721
126 0.2249123
127 NA
128 0.9799679
129 0.8824944
130 0.5184474
131 0.6629231
132 2.5369853
133 2.1741571
134 NA
135 NA
136 0.7410472
137 1.0322271
138 0.2793670
139 NA
140 0.6567876
141 0.3956591
142 0.5041533
143 1.2155895
144 0.5723100
145 1.4353883
146 0.8992330
147 NA
148 1.2331454
149 1.5480950
150 1.2412610
151 1.7478419
152 0.2592951
153 NA
154 NA
155 0.7886661
156 1.3936918
157 0.7299561
158 1.6610981
159 0.3894158
160 0.4153104
161 0.6263585
162 1.3388882
163 0.8066189
164 0.1223859
165 0.1391880
166 1.1442708
167 0.3239671
168 0.5980652
169 2.4539844
170 NA
171 NA
172 NA
173 1.4054565
174 0.5336988
175 0.4282792
176 0.6808409
177 0.4381447
178 0.8371536
179 0.8970005
180 0.3541814
181 1.0359298
182 0.1809903
183 0.8341847
184 NA
185 NA
186 0.6272029
187 0.7288299
188 0.6426964
189 0.6384224
190 NA
191 0.3970060
192 1.2393974
193 4.8871651
194 0.6345090
195 0.6128592
196 0.8079204
197 1.2318939
198 0.1876111
199 1.6844744
200 NA
201 0.6862876
202 0.6768210
203 1.1407441
204 0.2547175
205 0.3182180# Looking at average score for each country
SPI %>%
group_by(`Country`) %>%
dplyr::summarise(mean = mean(`Environment`))
# A tibble: 205 × 2
Country mean
<chr> <dbl>
1 Albania 71.0
2 Algeria 51.7
3 American Samoa NA
4 Andorra NA
5 Angola 62.9
6 Antigua and Barbuda NA
7 Argentina 78.0
8 Armenia 58.3
9 Australia 85.1
10 Austria 83.4
# … with 195 more rowsVisualizations
Average scores worldwide by year
By looking at how the world is doing as a whole from 2011-2021, we can get an idea of what the improvement overall has been like and compare that to individual countries’ progress. These graphs have been changed and now show the standard error bars.
# Seeing if average Access to Knowledge scores are changing over time
avgAK <- summarySE(SPI, measurevar="Access-knowledge", groupvars=c("Year"),
na.rm=TRUE)
avgAK %>%
ggplot(aes(x=Year, y=`Access-knowledge`)) +
geom_errorbar(aes(ymin=`Access-knowledge`-se, ymax=`Access-knowledge`+se),
width=.1, color="blue") +
geom_line(color="dark blue") +
geom_point(color="dark blue") +
labs(y="Avg Access to Knowledge")
# What about Access to Information and Communications?
avgIC <- summarySE(SPI, measurevar="Info-comm", groupvars=c("Year"), na.rm=TRUE)
avgIC %>%
ggplot(aes(x=Year, y=`Info-comm`)) +
geom_errorbar(aes(ymin=`Info-comm`-se, ymax=`Info-comm`+se), width=.1,
color="red") +
geom_line(color="dark red") +
geom_point(color="dark red") +
labs(y="Avg Info and Communications")
# Looking at Health and Wellness
avgHW <- summarySE(SPI, measurevar="Health", groupvars=c("Year"), na.rm=TRUE)
avgHW %>%
ggplot(aes(x=Year, y=`Health`)) +
geom_errorbar(aes(ymin=`Health`-se, ymax=`Health`+se), width=.1,
color="#b4a7d6") +
geom_line(color="#4d1c7c") +
geom_point(color="#4d1c7c") +
labs(y="Avg Health and Wellness")
# Lastly, looking at Environmental Quality
avgEQ <- summarySE(SPI, measurevar="Environment", groupvars=c("Year"),
na.rm=TRUE)
avgEQ %>%
ggplot(aes(x=Year, y=`Environment`)) +
geom_errorbar(aes(ymin=`Environment`-se, ymax=`Environment`+se), width=.1,
color="#93c47d") +
geom_line(color="#274e13") +
geom_point(color="#274e13") +
labs(y="Avg Environemtnal Quality")
All of these plots show that there has been improvement across all categories, but not all of them have been consistent and they have all been exponential. Something left out is how each country has improved over the years. I also could have chosen a different metric, such as a median, which can give a different type of insight since means may be skewed due to outliers. Additionally, there aren’t a lot of years included in the dataset compared to the length of human history, so some more historical data could be valuable.
Variation by Country
Since there are a great many countries in the dataset and I don’t want there to be an overcrowded graph, I will select a few countries to look at. I’ll base my selection on the largest countries by population in their respective continent so there is some similarity between them: China, Russia, the United States, Brazil, Nigeria, and Australia.
SPI_Large <- SPI %>%
filter(`Country` %in% c("China", "Russia", "Brazil", "Nigeria", "Australia",
"United States"))
head(SPI_Large)
# A tibble: 6 × 74
Rank Country Code Year Status SPI Needs Wellbeing Opportunity
<dbl> <chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl>
1 11 Australia AUS 2021 Ranked 90.3 95.1 90.4 85.3
2 10 Australia AUS 2020 Ranked 90.1 95.1 90.5 84.8
3 12 Australia AUS 2019 Ranked 90 95 90.2 84.8
4 11 Australia AUS 2018 Ranked 89.9 94.6 90.6 84.5
5 10 Australia AUS 2017 Ranked 90.0 95.1 90.2 84.6
6 10 Australia AUS 2016 Ranked 89.8 95.2 89.9 84.5
# … with 65 more variables: `Nutrition/care` <dbl>, Sanitation <dbl>,
# Shelter <dbl>, Safety <dbl>, `Access-knowledge` <dbl>,
# `Info-comm` <dbl>, Health <dbl>, Environment <dbl>, Rights <dbl>,
# Choice <dbl>, Inclusiveness <dbl>, `Advanced-ed` <dbl>,
# Infectious <dbl>, `Child mortality` <dbl>, Stunting <dbl>,
# `Maternal-mortality` <dbl>, Undernourishment <dbl>,
# `Improved-sanitation` <dbl>, `Improved-water` <dbl>, …By looking at overall rankings over time, there can be a good general idea how these coutries have done in comparison to the others in all indicators, not just a few.
ggplot(data = SPI_Large, mapping=aes(x = `Year`, y = `Rank`, color = `Country`)) +
geom_line() +
facet_wrap(facets = vars(`Country`))
(it is important to note that a low rank means the country is doing better than the others and a higher number means it is doing worse)
From the above, we can see that Nigeria has consistently ranked very poorly with very little improvement. Brazil had a slightly better-than-middle ranking, but then was suddenly ranked worse in 2017 and continued to trend poorer every year since. China and Russia, on the other hand, seem pretty stagnant with consistent rankings throughout the years–China doing worse than Russia. Australia has the best consistent rankings out of all the countries, while the US was a close second but has started to be ranked poorly in 2015 or so and on. I think it’s interesting to look at these comparisons when thinking about overall rankings because it makes me wonder what is dragging down or boosting up scores for each country. Something left unanswered is what other countries in the same continent are like for rankings, what caused these rankings to drop, and what categories some countries do better in than others. A general view is helpful but does not tell everything.
Research Questions:
Have the average worldwide scores for Wellbeing categories improved over time? What countries have improved the most or the least?
Do countries that have higher Wellbeing scores have higher scores in other categories? How do the Wellbeing scores relate to rank?
How to large countries from each contient compare?
New Visualizations
# Boxplot of the Large Countries' Wellbeing Scores
SPI_Large %>%
ggplot(mapping=aes(x=Country, y=Wellbeing, fill=Country)) +
geom_boxplot() +
labs(y="Wellbeing Score")
I think so far in my analysis, I am missing more information on whether or not countries’ Wellbeing scores correlate with their Rank (if countries that do better in overall Wellbeing have better Rankings). Right now, I can see that the average worldwide statistics have mostly improved since 2011, though there are some variables that fluctuate a bit more (such as Environmental Quality). Additionally, the larger countries have generally consistent rankings, showing that these worldwide improvements have most likely taken place in other countries. I don’t know if a naive reader would need much else to understand the graphs–if anything, they might need mre information about the Social Progress Index itself and what the variables mean. I would want to answer the question of why certain countries have improved more or less than others in different variables or their overall rankings, but the “why” factor isn’t something present in the dataset.
