95% Confidence Interval for Mean
Lower Bound
29,378
Upper Bound
34,169
5% Trimmed Mean
31,520
Median
31,200
Variance
175,646
Std. Deviation
13,253
Minimum
9,500
Maximum
59,300
Range
49,800
Interquartile Range
21,330
Skewness
0,259
Kurtosis
-0,895
Глобальный индекс подключения
Global connectivity index
GCI
Mean
47,440
95% Confidence Interval for Mean
Lower Bound
43,360
Upper Bound
51,520
5% Trimmed Mean
47,120
Median
45,500
Variance
205,802
Std. Deviation
14,346
Minimum
23,000
Maximum
77,000
Range
54,000
Interquartile Range
27,000
Skewness
0,298
Таблица 31. Матрица коэффициентов корреляции Пирсона
|
HDI |
LE |
EYS |
MYS |
lnGNI |
NRI |
pil1 |
pil2 |
pil3 |
pil4 |
pil5 |
pil6 |
pil7 |
pil8 |
pil9 |
pil10 |
wellbeing |
inequality |
footprint |
HPI |
HLY |
GCI |
||
|
HDI |
1 |
,899** |
,926** |
,910** |
,947** |
,891** |
,630** |
,790** |
,908** |
,558** |
,914** |
,931** |
,718** |
,643** |
,766** |
,776** |
,760** |
-,952** |
,753** |
,308** |
,902** |
,894** |
|
|
LE |
,899** |
1 |
,809** |
,732** |
,790** |
,798** |
,525** |
,704** |
,807** |
,579** |
,793** |
,813** |
,633** |
,592** |
,679** |
,717** |
,677** |
-,927** |
,616** |
,499** |
,870** |
,745** |
|
|
EYS |
,926** |
,809** |
1 |
,839** |
,831** |
,819** |
,586** |
,726** |
,857** |
,507** |
,846** |
,858** |
,648** |
,562** |
,700** |
,709** |
,707** |
-,876** |
,677** |
,261** |
,839** |
,763** |
|
|
MYS |
,910** |
,732** |
,839** |
1 |
,810** |
,819** |
,575** |
,734** |
,825** |
,496** |
,894** |
,847** |
,675** |
,559** |
,722** |
,703** |
,660** |
-,853** |
,705** |
,187* |
,779** |
,876** |
|
|
lnGNI |
,947** |
,790** |
,831** |
,810** |
1 |
,850** |
,638** |
,754** |
,869** |
,477** |
,845** |
,908** |
,692** |
,643** |
,727** |
,738** |
,770** |
-,892** |
,786** |
,211* |
,871** |
,846** |
|
|
NRI |
,891** |
,798** |
,819** |
,819** |
,850** |
1 |
,856** |
,909** |
,915** |
,560** |
,861** |
,932** |
,899** |
,855** |
,925** |
,939** |
,747** |
-,876** |
,778** |
,213* |
,879** |
,953** |
|
|
pil1 |
,630** |
,525** |
,586** |
,575** |
,638** |
,856** |
1 |
,806** |
,714** |
,253** |
,644** |
,719** |
,873** |
,806** |
,844** |
,819** |
,598** |
-,610** |
,655** |
,049 |
,676** |
,838** |
|
|
pil2 |
,790** |
,704** |
,726** |
,734** |
,754** |
,909** |
,806** |
1 |
,809** |
,383** |
,784** |
,827** |
,816** |
,785** |
,831** |
,860** |
,617** |
-,767** |
,677** |
,151 |
,747** |
,803** |
|
|
pil3 |
,908** |
,807** |
,857** |
,825** |
,869** |
,915** |
,714** |
,809** |
1 |
,476** |
,829** |
,924** |
,791** |
,669** |
,836** |
,789** |
,752** |
-,867** |
,779** |
,187* |
,879** |
,921** |
|
|
pil4 |
,558** |
,579** |
,507** |
,496** |
,477** |
,560** |
,253** |
,383** |
,476** |
1 |
,499** |
,495** |
,350** |
,417** |
,401** |
,501** |
,430** |
-,621** |
,400** |
,317** |
,538** |
,146 |
|
|
pil5 |
,914** |
,793** |
,846** |
,894** |
,845** |
,861** |
,644** |
,784** |
,829** |
,499** |
1 |
,858** |
,688** |
,638** |
,718** |
,764** |
,661** |
-,888** |
,686** |
,261** |
,803** |
,817** |
|
|
pil6 |
,931** |
,813** |
,858** |
,847** |
,908** |
,932** |
,719** |
,827** |
,924** |
,495** |
,858** |
1 |
,793** |
,708** |
,847** |
,827** |
,763** |
-,902** |
,811** |
,173 |
,893** |
,919** |
|
|
pil7 |
,718** |
,633** |
,648** |
,675** |
,692** |
,899** |
,873** |
,816** |
,791** |
,350** |
,688** |
,793** |
1 |
,756** |
,950** |
,821** |
,704** |
-,700** |
,683** |
,170 |
,785** |
,897** |
|
|
pil8 |
,643** |
,592** |
,562** |
,559** |
,643** |
,855** |
,806** |
,785** |
,669** |
,417** |
,638** |
,708** |
,756** |
1 |
,760** |
,949** |
,551** |
-,649** |
,590** |
,178 |
,657** |
,699** |
|
|
pil9 |
,766** |
,679** |
,700** |
,722** |
,727** |
,925** |
,844** |
,831** |
,836** |
,401** |
,718** |
,847** |
,950** |
,760** |
1 |
,838** |
,714** |
-,758** |
,747** |
,135 |
,822** |
,942** |
|
|
pil10 |
,776** |
,717** |
,709** |
,703** |
,738** |
,939** |
,819** |
,860** |
,789** |
,501** |
,764** |
,827** |
,821** |
,949** |
,838** |
1 |
,656** |
-,789** |
,670** |
,243** |
,781** |
,819** |
|
|
wellbeing |
,760** |
,677** |
,707** |
,660** |
,770** |
,747** |
,598** |
,617** |
,752** |
,430** |
,661** |
,763** |
,704** |
,551** |
,714** |
,656** |
1 |
-,747** |
,669** |
,447** |
,931** |
,731** |
|
|
inequality |
-,952** |
-,927** |
-,876** |
-,853** |
-,892** |
-,876** |
-,610** |
-,767** |
-,867** |
-,621** |
-,888** |
-,902** |
-,700** |
-,649** |
-,758** |
-,789** |
-,747** |
1 |
-,719** |
-,401** |
-,916** |
-,828** |
|
|
footprint |
,753** |
,616** |
,677** |
,705** |
,786** |
,778** |
,655** |
,677** |
,779** |
,400** |
,686** |
,811** |
,683** |
,590** |
,747** |
,670** |
,669** |
-,719** |
1 |
-,194* |
,746** |
,882** |
|
|
HPI |
,308** |
,499** |
,261** |
,187* |
,211* |
,213* |
,049 |
,151 |
,187* |
,317** |
,261** |
,173 |
,170 |
,178 |
,135 |
,243** |
,447** |
-,401** |
-,194* |
1 |
,444** |
-,171 |
|
|
HLY |
,902** |
,870** |
,839** |
,779** |
,871** |
,879** |
,676** |
,747** |
,879** |
,538** |
,803** |
,893** |
,785** |
,657** |
,822** |
,781** |
,931** |
-,916** |
,746** |
,444** |
1 |
,858** |
|
|
GCI |
,894** |
,745** |
,763** |
,876** |
,846** |
,953** |
,838** |
,803** |
,921** |
,146 |
,817** |
,919** |
,897** |
,699** |
,942** |
,819** |
,731** |
-,828** |
,882** |
-,171 |
,858** |
1 |
Таблица 32. Состав кластеров
|
Кластер 1 |
Кластер 2 |
Кластер 3 |
|
|
Albania |
Algeria |
Australia |
|
|
Armenia |
Angola |
Austria |
|
|
Azerbaijan |
Bangladesh |
Bahrain |
|
|
Bhutan |
Bolivia (Plurinational State of) |
Barbados |
|
|
Brazil |
Botswana |
Belgium |
|
|
Bulgaria |
Burkina Faso |
Canada |
|
|
Cabo Verde |
Burundi |
Czech Republic |
|
|
Chile |
Cambodia |
Denmark |
|
|
China |
Cameroon |
Estonia |
|
|
Colombia |
Chad |
Finland |
|
|
Costa Rica |
Cфte d'Ivoire |
France |
|
|
Croatia |
Ethiopia |
Germany |
|
|
Cyprus |
Gabon |
Hong Kong, China (SAR) |
|
|
Egypt |
Gambia |
Iceland |
|
|
El Salvador |
Ghana |
Ireland |
|
|
Georgia |
Guatemala |
Israel |
|
|
Greece |
Guinea |
Japan |
|
|
Hungary |
Haiti |
Korea (Republic of) |
|
|
India |
Honduras |
Latvia |
|
|
Indonesia |
Lao People's Democratic Republic |
Lithuania |
|
|
Iran (Islamic Republic of) |
Lesotho |
Luxembourg |
|
|
Italy |
Libya |
Malaysia |
|
|
Jamaica |
Madagascar |
Malta |
|
|
Jordan |
Malawi |
Netherlands |
|
|
Kazakhstan |
Mali |
New Zealand |
|
|
Kuwait |
Mauritania |
Norway |
|
|
Kyrgyzstan |
Mozambique |
Portugal |
|
|
Lebanon |
Namibia |
Qatar |
|
|
Mauritius |
Nepal |
Saudi Arabia |
|
|
Mexico |
Nicaragua |
Singapore |
|
|
Moldova (Republic of) |
Nigeria |
Slovenia |
|
|
Mongolia |
Pakistan |
Spain |
|
|
Montenegro |
Rwanda |
Sweden |
|
|
Morocco |
Senegal |
Switzerland |
|
|
Oman |
Suriname |
United Arab Emirates |
|
|
Panama |
Swaziland |
United Kingdom |
|
|
Peru |
Tajikistan |
United States |
|
|
Philippines |
Tanzania (United Republic of) |
||
|
Poland |
Timor-Leste |
||
|
Romania |
Uganda |
||
|
Russian Federation |
Yemen |
||
|
Serbia |
Zambia |
||
|
Seychelles |
|||
|
Slovakia |
|||
|
South Africa |
|||
|
Sri Lanka |
|||
|
Thailand |
|||
|
Trinidad and Tobago |
|||
|
Tunisia |
|||
|
Turkey |
|||
|
Ukraine |
|||
|
Uruguay |
|||
|
Venezuela (Bolivarian Republic of) |
|||
|
Viet Nam |
|||
|
Dominican Republic |
|||
|
Guyana |
|||
|
Kenya |
|||
|
Paraguay |
Таблица 33. Матрица корреляций дискриминантного анализа
|
pil1 |
pil2 |
pil3 |
pil4 |
pil5 |
pil6 |
pil7 |
pil8 |
pil9 |
pil10 |
||
|
pil1 |
1,000 |
,520 |
,195 |
-,077 |
,282 |
,226 |
,635 |
,576 |
,529 |
,586 |
|
|
pil2 |
,520 |
1,000 |
,300 |
-,098 |
,384 |
,341 |
,453 |
,410 |
,442 |
,518 |
|
|
pil3 |
,195 |
,300 |
1,000 |
,072 |
,447 |
,643 |
,287 |
,001 |
,362 |
,165 |
|
|
pil4 |
-,077 |
-,098 |
,072 |
1,000 |
-,051 |
,040 |
,053 |
,061 |
,117 |
,120 |
|
|
pil5 |
,282 |
,384 |
,447 |
-,051 |
1,000 |
,485 |
,265 |
,051 |
,262 |
,212 |
|
|
pil6 |
,226 |
,341 |
,643 |
,040 |
,485 |
1,000 |
,296 |
,084 |
,416 |
,256 |
|
|
pil7 |
,635 |
,453 |
,287 |
,053 |
,265 |
,296 |
1,000 |
,375 |
,811 |
,476 |
|
|
pil8 |
,576 |
,410 |
,001 |
,061 |
,051 |
,084 |
,375 |
1,000 |
,340 |
,888 |
|
|
pil9 |
,529 |
,442 |
,362 |
,117 |
,262 |
,416 |
,811 |
,340 |
1,000 |
,465 |
|
|
pil10 |
,586 |
,518 |
,165 |
,120 |
,212 |
,256 |
,476 |
,888 |
,465 |
1,000 |
Таблица 34. Коэффициенты корреляции Спирмена
|
age |
fb_use |
gender |
happiness |
int_use |
marital |
mat_satisfaction |
pc_use |
satisfaction |
vk_use |
||
|
Age |
1,000 |
,020 |
,142** |
,261** |
,550** |
,630** |
-,028** |
,526** |
,163** |
,385** |
|
|
fb_use |
,020 |
1,000 |
,032* |
-,001 |
. |
,037* |
,085** |
,053** |
,045** |
,114** |
|
|
Gender |
,142** |
,032* |
1,000 |
,071** |
,054** |
,237** |
,000 |
,052** |
,039** |
,080** |
|
|
Happiness |
,261** |
-,001 |
,071** |
1,000 |
,257** |
,213** |
,247** |
,249** |
,510** |
,099** |
|
|
int_use |
,550** |
. |
,054** |
,257** |
1,000 |
,360** |
,001 |
,883** |
,186** |
. |
|
|
Marital |
,630** |
,037* |
,237** |
,213** |
,360** |
1,000 |
,033** |
,335** |
,136** |
,270** |
|
|
mat_satisfaction |
-,028** |
,085** |
,000 |
,247** |
,001 |
,033** |
1,000 |
,006 |
,468** |
,028 |
|
|
pc_use |
,526** |
,053** |
,052** |
,249** |
,883** |
,335** |
,006 |
1,000 |
,184** |
,048** |
|
|
Satisfaction |
,163** |
,045** |
,039** |
,510** |
,186** |
,136** |
,468** |
,184** |
1,000 |
,084** |
|
|
vk_use |
,385** |
,114** |
,080** |
,099** |
. |
,270** |
,028 |
,048** |
,084** |
1,000 |