Effect of GDP per Capita on Life Expectancy in Asia, Europe and Africa

This study analyzes the relationship between GDP per Capita and life expectancy in Asia, Europe and Africa. The study uses scatter graphs, bar graphs, standard deviation and regression analysis to prove the hypothesis. The study reveals a positive impact of per capita GDP on life expectancy.

Effect of GDP per Capita (Purchasing
Power Parity/PPP)
On Life Expectancy
Introduction
Hypothesis: Relationship between GDP and life expectancy between genders in Asia,
Europe and Africa.
For my math studies project I am going find, if there are relation between PPP also known as
GDP and life expectancy is under observation considering two genders separately. In this
work I’ll trying to understand if there is positive relation between per capita GDP and life
expectancy of people.
The data for GDP and life expectancy was taken from the World Bank, the data is from 2015.
I will be using several mathematical processes to prove or disprove my hypothesis. The lower
process will be the scatter graph, bar graph and standard deviation (S.D). Lower processes
like scatter graph will be used in order to find the correlation between GDP and life
expectancy. The higher level process will be Regression Analysis (curve of best fit)
Mathematical Processes
Summary statistics of the variables
Africa: The means for per capita GDP, male life expectancy and female life expectancy were
found. Initially the frequency table for per capita GDP was found as in figure 1.

Figure 1: Per Capita GDP frequency distribution
The GDP wise country division was represented by a bar diagram. The distribution reflected
that most of the countries were in GDP per capita bracket of $ 750 to $ 3400.
Figure 2: Countries as par GDP per capita-Africa
The average GDP per capita was calculated as
= $5677.01. Average GDP was calculated
using Male life expectancy data on Africa which has been included in the master table.

The average male life expectancy was calculated as
Male Life Expec tan cy = Sum of life lenght of countries
Total number of countries =3002. 42
49 = 61.27. The average female
life expectancy was
Female Life Expec tan cy= Sum of life of females
Total number of countries =3181. 56
49 = 64.92
persons. The standard deviations (S.D) were respectively {using the formula
s= √ ∑ x2
n −( ∑ x
n )
2
} $6270.43, 6.08 and 6.72 persons (appendix table 10). The S.D value
for GDP indicated the huge disparity among the countries. The accumulation of the per capita
GDP was in the range (mean S.D), which was calculated as -$593.42 to $11947.44.
Between this limits there were 43 countries, hence
42
63 X 100=66 .67 % countries lied in the
interval.
Asia: The means for per capita GDP, male life expectancy and female life expectancy were
found. The frequency distribution has been provided in figure 3. The limits are GDP per
capita and unit was dollars.
Table 1: Frequency distribution for Asia
Lower
Limit
Upper
Limit Frequency
700 12200 16
12200 23700 7
23700 35200 4
35200 46700 3
46700 58200 2
58200 69700 2
69700 81200 2
81200 92700 0
92700 104200 1
104200 115700 0
115700 127200 1

The frequency distribution has been represented in bar diagram in figure 3. The distribution
curve was right skewed.
Figure 3: Countries as par GDP per capita-Africa
The average GDP per capita was calculated as
Avg GDP= Total GDP
Number of countries = $ 1060556 . 65
38 = $ 27909.38. Male life expectancy data
from master data was used. The average male life expectancy was calculated as
Male Life Expec tan cy = Sum of life lenght of countries
Total number of countries =2740 .63
38 = 72.12 persons. The standard
deviations (S.D) {using the formula
s= √ ∑ x2
n −( ∑ x
n )
2
} were respectively $ 29321.80,
6.03 and 6.49 persons (appendix table 11). From the mean GDP value compared to Africa
was much higher because of large number of developed and developing countries in Asia.
The average female life expectancy was
Female Life Expec tan cy= Sum of life of females
Total number of countries =2898 .38
38 = 76.27 persons.

The accumulation of the per capita GDP was in the range (mean S.D), which was
calculated as -$1412.41 to $57,231.18. Between this limits there were 33 countries, hence
33
38 X 100=86 . 84 % countries lied in the interval.
The disparity in GDP was also prominent from the S.D value. Mean life expectancy rates of
72.12 and 76.27 for males and females were also higher compared to African life expectancy
values. Total 38 countries were studied under Asia.
Europe: The frequency distribution has been provided in figure 4. The limits are GDP per
capita and unit was dollars.
Table 2: Frequency distribution of countries-Europe
Lower Limit Upper
Limit Frequency
10750 19050 5
19050 27350 6
27350 35650 6
35650 43950 6
43950 52250 4
52250 60550 1
60550 68850 2
68850 77150 0
77150 85450 0
85450 93750 0
93750 102050 1
The frequency distribution has been represented in bar diagram in figure 3. The distribution
curve revealed that countries in Europe were distributed comparatively in even manner based
on GDP per capita.

Figure 4: Countries as per GDP per capita-Europe
The average GDP per capita was calculated as
Avg GDP= Total GDP
Number of countries = $ 1098842. 96
31 = $35446.54. Male life expectancy data
from master data was used for this calculation. The average male life expectancy was
calculated as
Male Life Expec tan cy = Sum of life lenght of countries
Total number of countries =2404 . 24
31 = 77.55 persons.
The S.D value {using the formula
s= √ ∑ x2
n −( ∑ x
n )
2
} was $17830.91 (table 12 in
Appendix) and the value suggested that the continent was having countries with very close
values of GDP level. High GDP influencing life expectancy rates to move to the greater sides
were also visible. Total 31 countries were studies within Europe.
The average female life expectancy was
Female Life Expec tan cy= Sum of life of females
Total number of countries =2566. 82
31 = 82.8 persons.

Mean GDP for the continent was highest among the three continents. Life expectancy rates
for males and females on average were and which were also the highest in the study.
Scatter graphs
Africa:
The continent with 49 countries has the most skewed data among all three continents.
Figure 7: Scatter diagram for male life expectancy in Africa
Scatter plot was indicative of the fact that major number of countries were condensed within
$ 7000 GDP values and average life expectancy were positive but not on the higher side.

Figure 8: Scatter diagram for female life expectancy in Africa
Female life expectancy was also not very promising. Major points in the data were between
50 years to 65 years of age group, for low GDP countries.
Asia: The continent had 38 countries in the study.
Figure 9: Scatter diagram for male life expectancy in Asia
GDP clustering in Asia is also on the lower side below $30000 but better than African
continent.

Clustering for life expectancy was between 65 years to 75 years. Level of correlation was
positive and high. It was also observed that life expectancy was over 75 years in the countries
having more than $50000 GDP per capita.
Figure 10: Scatter diagram for female life expectancy in Asia
Female life expectancy was also clustered in the age bracket of 65 years and 80 years. The
female group also had lower life expectancy range compared to males in Asia for higher level
GDP countries.
Europe: The continent had 31 countries in the study.

Figure 11: Scatter diagram for male life expectancy in Europe
GDP clustering in Europe was the best of the three continents. Clustering for life expectancy
was between 70 years to 80 years. Level of correlation was positive and very high. It was also
observed that life expectancy was near 80 years in the countries having more than $50000
GDP per capita.
Figure 12: Scatter diagram for female life expectancy in Asia
Female life expectancy was also clustered in the age bracket of 77 years and 85 years. The
female group also had a high life expectancy range compared to males in Europe for higher
level GDP countries

Regression line (line of best fit

Table 3: Africa Descriptive table
AFRICA 2015/GDP(in $)X
MALE/LIFE
EXPECTANCY
(Y)
FEMALE/LIFE
EXPECTANCY
(Z)
sum 278173.52 3002.40 3181.53
square 3505788848.24 185779.00 208784.11
n 49 49 49
SD 6270.43 6.08 6.72
MEAN 5677.01 61.27 64.93
The SD value in table 3 was calculated using the formula
s= √ ∑ x2
n −( ∑ x
n )
2
and the mean
was calculated using the formula x
−
= ∑ x
n .
Africa: The regression equation for y on x is y=a+bx , where
b=
∑
i=1
n
( xi −x
−
)∗( yi − y
−
)
∑
i=1
n
( xi−x
−
)2
and a=∑ y−b∗∑ x
n .
Hence,
b=700542. 95
1926595316. 79 =0 .00036 and
a=3002. 42−0 .00036∗278173 .51
51 =56 . 91
The regression line for males was y=0 . 00036 x+ 56. 91
The regression line for predicting life expectancy based on GDP was found. For linear
regression model line of best fit is found as ( y − y
−
) =b yx ( x −x
−
) .
The above calculation was done using table 3 and table 5. The regression coefficient was
where r is the correlation coefficient.
, were the standard deviation of life expectancy and PPP (GDP per capita).

Asia: The regression line for predicting life expectancy based on GDP was found. For
linear regression model line of best fit is found as .
The regression coefficient was where r is the correlation coefficient.
, were the standard deviation of life expectancy and PPP (GDP per capita).
For male population
b yx =r σ y
σ x
=0 . 771∗ 6 . 03
29321. 80 =0 . 0002
The above calculations was done using values from tables 6 and 11 (appendix).
The regression line for males was
For female population
b yx =r σ y
σ x
=0 . 72∗ 6 . 49
29321. 80 =0 . 0002
The above calculations was done using values from tables 7 and 11 (appendix).
The regression line for females was
Europe: The regression line for predicting life expectancy based on GDP was found. For
linear regression model line of best fit is found as .

The regression coefficient was where r is the correlation coefficient.
, were the standard deviation of life expectancy and PPP (GDP per capita).
For male population
b yx =r σ y
σ x
=0 . 785∗ 3 .11
17540 . 96 =0 .0001
The above calculations was done using values from tables 8 and 12 (appendix).
The regression line for males was
( y−77 . 56 ) =0. 0001 ( x−35446 .55 ) => y=0 . 0001 x +81 . 09
For female population
b yx =r σ y
σ x
=0 . 784∗ 2. 52
17540. 96 =0 . 0001
The above calculations was done using values from tables 9 and 13 (appendix).
The regression line for females was
( y−82 . 80 ) =0 . 0001 ( x−35446 .55 ) => y=0 . 0001 x +86 . 34
Conclusion
According to the regression analysis of the study found the positive impact of per
capita GDP on life expectancy. Continent wise analysis revealed Africa as a wide spread
GDP per capita continent which was a little bit skewed due to outlier values. Asia and
Europe were ahead of Africa in terms of GDP per capita clustering. Europe was symmetrical
among the three continents with respect to GDP per capita income clustering. Gender wise
analysis revealed that females have a longer life span given the comforts of life. This was

true for all three continents and especially for higher per capita GDP countries. The
regression lines indicated that the increase of GDP per capita will affect the life expectancy
positively with a factor almost near to zero up to four decimal places. The results were
totally in accordance to earlier research works given in literature review. The positive
correlations were increasing in every case till a certain threshold for each and every
combination of study. Hence per capita GDP was the reason for increase in life expectancy
up to certain level for each country. Consideration of other factors such as education, public
health could intensify the research work in practical aspect.
Raw data
Master data for African continent from World Bank database
Country CONTINENT 2015/GDP(in
$)
MALE/LIFE
EXPECTANCY(years)
FEMALE/LIFE
EXPECTANCY(years)
Congo, Dem. Rep. AFRICA 750.50 57.74 60.68
Liberia AFRICA 785.25 61.05 62.96
Niger AFRICA 904.58 58.72 60.70
Malawi AFRICA 1088.70 60.04 65.17
Mozambique AFRICA 1118.22 55.54 59.78
Sierra Leone AFRICA 1315.97 50.87 51.99
Togo AFRICA 1349.37 59.15 60.73
Madagascar AFRICA 1377.17 64.00 67.09
Comoros AFRICA 1413.06 61.81 65.20
Guinea-Bissau AFRICA 1446.47 55.27 58.72
Ethiopia AFRICA 1533.11 63.20 66.91
Gambia, The AFRICA 1568.02 59.66 62.33
Burkina Faso AFRICA 1596.33 59.19 60.53
Uganda AFRICA 1665.95 57.36 61.77
Rwanda AFRICA 1715.89 64.56 68.79
Guinea AFRICA 1753.06 58.92 59.91
Zimbabwe AFRICA 1912.28 58.59 62.05
Mali AFRICA 1919.23 56.79 58.16
Benin AFRICA 1987.17 59.13 62.11
Chad AFRICA 2047.64 51.37 53.80
Somalia AFRICA 2053.44 69.02 72.00
Senegal AFRICA 2293.85 64.74 68.68
Tanzania AFRICA 2490.96 63.08 66.82
Lesotho AFRICA 2708.15 51.27 55.98
Kenya AFRICA 2835.64 64.29 69.12

Djibouti AFRICA 3139.27 60.64 63.94
Cote d'Ivoire AFRICA 3241.61 51.63 54.60
Cameroon AFRICA 3289.06 56.40 58.78
Mauritania AFRICA 3601.61 61.60 64.56
Zambia AFRICA 3627.20 58.90 63.90
Ghana AFRICA 3929.68 61.44 63.43
Sudan AFRICA 4290.37 62.71 65.83
Congo, Repub. of the AFRICA 5542.89 62.52 65.74
Nigeria AFRICA 5670.64 52.24 53.76
Burundi AFRICA 5918.59 70.50 74.47
Angola AFRICA 6231.07 58.42 64.09
Morocco AFRICA 7296.93 74.41 76.69
Swaziland AFRICA 7758.50 53.67 60.32
Namibia AFRICA 9964.22 60.83 66.58
Egypt AFRICA 10095.61 69.14 73.56
Tunisia AFRICA 10749.86 73.52 77.57
St Pierre & Miquelon AFRICA 11954.36 72.64 78.06
South Africa AFRICA 12362.58 58.46 65.58
Algeria AFRICA 13724.72 74.67 77.10
Botswana AFRICA 15356.46 62.94 68.71
Gabon AFRICA 16836.61 64.16 67.28
Mauritius AFRICA 18864.11 71.08 77.79
Seychelles AFRICA 25524.96 68.40 78.30
Equatorial Guinea AFRICA 27572.59 56.14 58.94
Master data for Asian continent from World Bank database
Country CONTINEN
T
2015/GDP(in
$)
MALE/LIFE
EXPECTANCY(years)
FEMALE/LIFE
EXPECTANCY(years)
Afghanistan ASIA 1809.02 62.05 64.61
Bangladesh ASIA 3132.57 70.59 73.94
Bhutan ASIA 7743.34 69.59 70.03
Brunei ASIA 74600.16 75.46 78.76
Burma ASIA 748.42 55.14 59.09
Cambodia ASIA 3290.95 66.47 70.57
China ASIA 13569.89 74.64 77.67
Hong Kong ASIA 53595.24 81.40 87.30
India ASIA 5754.06 66.86 69.88
Indonesia ASIA 10367.70 67.00 71.18
Iran ASIA 16500.90 74.67 76.87
Japan ASIA 37818.09 80.79 87.05
Korea, South ASIA 34177.65 78.99 85.48
Laos ASIA 5755.06 64.81 67.84
Macau ASIA 100444.56 80.71 86.62
Malaysia ASIA 25001.61 73.01 77.54
Maldives ASIA 13705.01 76.11 78.18

Mongolia ASIA 11411.94 65.09 73.34
Nepal ASIA 2314.27 68.32 71.49
Pakistan ASIA 4695.70 65.38 67.33
Philippines ASIA 6874.58 65.68 72.50
Singapore ASIA 80892.06 80.40 84.90
Sri Lanka ASIA 11196.40 71.71 78.44
Thailand ASIA 15236.71 71.37 78.95
Vietnam ASIA 5554.86 71.30 80.71
Bahrain ASIA 43926.47 75.93 77.84
Cyprus ASIA 30549.10 78.15 82.54
Iraq ASIA 14928.89 67.48 71.90
Israel ASIA 32024.35 80.10 84.10
Jordan ASIA 8491.05 72.53 75.93
Kuwait ASIA 68476.33 73.70 75.85
Lebanon ASIA 13352.71 77.79 81.29
Oman ASIA 40138.95 75.08 79.27
Qatar ASIA 119749.43 77.25 79.74
Saudi Arabia ASIA 50723.71 73.11 76.11
Turkey ASIA 23388.48 72.23 78.74
United Arab Emirates ASIA 65975.38 76.41 78.61
Yemen ASIA 2641.05 63.33 66.19
Master data for European continent from World Bank database
Country CONTINENT 2015/GDP(in
$)
MALE/LIFE
EXPECTANCY
(years)
FEMALE/LIFE
EXPECTANCY(years)
Bulgaria EUROPE 17000.17 71.10 78.00
Romania EUROPE 20545.08 71.40 78.70
Hungary EUROPE 25034.45 72.40 79.70
Serbia EUROPE 13277.80 73.00 78.10
Macedonia EUROPE 12759.82 73.56 77.59
Slovakia EUROPE 28308.88 73.70 80.90
Bosnia & Herzegovina EUROPE 10932.05 74.17 79.23
Croatia EUROPE 20759.05 74.30 80.40
Poland EUROPE 25299.97 74.40 82.20
Albania EUROPE 10971.29 76.21 80.30
Czech Republic EUROPE 30605.42 76.40 82.70
Slovenia EUROPE 29037.74 78.20 84.10
Portugal EUROPE 26607.83 78.40 84.80
Germany EUROPE 43937.95 78.70 83.60
Finland EUROPE 38885.90 78.80 84.10
Belgium EUROPE 41722.92 78.80 83.90
Greece EUROPE 24170.30 79.10 84.20
Denmark EUROPE 45458.70 79.10 83.20
Luxembourg EUROPE 94088.59 79.40 85.20

France EUROPE 37765.75 79.50 86.00
Austria EUROPE 44288.93 79.60 84.20
Ireland EUROPE 61543.21 79.60 83.50
Malta EUROPE 34272.75 79.80 84.20
United Kingdom EUROPE 38839.17 79.80 83.50
Netherlands EUROPE 46494.36 80.00 83.50
Norway EUROPE 64008.29 80.10 84.20
Spain EUROPE 32291.16 80.60 86.30
Sweden EUROPE 45679.28 80.60 84.60
Italy EUROPE 34317.57 81.10 86.00
Switzerland EUROPE 57264.16 81.10 85.40
Iceland EUROPE 42674.42 81.30 84.50
6.0 Appendix data
Table 4: Regression analysis for African males
Regression Statistics
Multiple R
0.50283858
4
R Square
0.25284664
1
Adjusted R
Square
0.22036171
3
Standard Error
5.42455639
6
Observations 49
Table 5: Regression analysis for African females
Regression Statistics
Multiple R 0.58321514
R Square
0.34013989
9
Adjusted R
Square
0.31145032
9
Standard Error
5.63123695
8
Observations 49

Table 6: Regression analysis for Asian males
Regression Statistics
Multiple R
0.77189199
5
R Square
0.59581725
2
Adjusted R
Square
0.57272109
5
Standard Error
3.99779812
4
Observations 38
Table 7: Regression analysis for Asian females
Regression Statistics
Multiple R
0.72031
8
R Square
0.51885
7
Adjusted R
Square
0.49136
4
Standard Error 4.69408
Observations 38
Table 8: Regression analysis for European males
Regression Statistics
Multiple R
0.78402266
7
R Square
0.61469154
2
Adjusted R
Square
0.58716950
9
Standard Error
2.02830520
2
Observations 31
Table 9: Regression analysis for European females
Regression Statistics
Multiple R 0.783664383

R Square 0.614129865
Adjusted R Square 0.586567713
Standard Error 1.64981712
Observations 31
Table 10: Africa data calculations
CONTINE
NT
2015/GDP
(in $) (X)
MALE/LIFE
EXPECTANCY
(Y)
FEMALE/
LIFE
EXPECTAN
CY (Z) X-SQUARE Y-SQUARE
Z-
SQUARE
AFRICA 750.50 57.74 60.68 563246.26 3334.14 3681.58
AFRICA 785.25 61.05 62.96 616612.67 3726.98 3963.71
AFRICA 904.58 58.72 60.70 818264.58 3447.69 3683.88
AFRICA 1088.70 60.04 65.17 1185271.62 3604.56 4247.65
AFRICA 1118.22 55.54 59.78 1250414.93 3084.69 3573.89
AFRICA 1315.97 50.87 51.99 1731786.34 2587.45 2702.54
AFRICA 1349.37 59.15 60.73 1820803.63 3498.96 3688.62
AFRICA 1377.17 64.00 67.09 1896592.29 4096.13 4501.07
AFRICA 1413.06 61.81 65.20 1996736.52 3820.23 4250.52
AFRICA 1446.47 55.27 58.72 2092271.55 3054.33 3447.92
AFRICA 1533.11 63.20 66.91 2350419.01 3994.24 4476.55
AFRICA 1568.02 59.66 62.33 2458695.86 3558.72 3884.41
AFRICA 1596.33 59.19 60.53 2548283.96 3503.57 3664.00
AFRICA 1665.95 57.36 61.77 2775389.09 3290.05 3815.04
AFRICA 1715.89 64.56 68.79 2944268.45 4167.48 4731.93
AFRICA 1753.06 58.92 59.91 3073230.29 3471.21 3588.61
AFRICA 1912.28 58.59 62.05 3656815.81 3433.14 3850.20
AFRICA 1919.23 56.79 58.16 3683437.73 3224.65 3382.93
AFRICA 1987.17 59.13 62.11 3948833.27 3496.59 3857.65
AFRICA 2047.64 51.37 53.80 4192818.02 2639.08 2893.90
AFRICA 2053.44 69.02 72.00 4216610.93 4764.31 5184.29
AFRICA 2293.85 64.74 68.68 5261764.06 4191.14 4716.94
AFRICA 2490.96 63.08 66.82 6204867.28 3978.58 4465.18
AFRICA 2708.15 51.27 55.98 7334068.51 2629.02 3133.87
AFRICA 2835.64 64.29 69.12 8040874.98 4133.46 4777.16
AFRICA 3139.27 60.64 63.94 9855038.33 3677.57 4087.94
AFRICA 3241.61 51.63 54.60 10508048.72 2665.45 2981.27
AFRICA 3289.06 56.40 58.78 10817945.59 3180.73 3454.50
AFRICA 3601.61 61.60 64.56 12971625.92 3794.68 4168.51
AFRICA 3627.20 58.90 63.90 13156594.65 3469.56 4082.95
AFRICA 3929.68 61.44 63.43 15442393.10 3774.50 4022.86
AFRICA 4290.37 62.71 65.83 18407294.04 3932.04 4333.46

AFRICA 5542.89 62.52 65.74 30723662.61 3908.75 4321.75
AFRICA 5670.64 52.24 53.76 32156151.69 2728.50 2889.92
AFRICA 5918.59 70.50 74.47 35029689.24 4970.53 5545.04
AFRICA 6231.07 58.42 64.09 38826208.32 3413.25 4108.04
AFRICA 7296.93 74.41 76.69 53245251.66 5536.25 5881.36
AFRICA 7758.50 53.67 60.32 60194253.40 2880.15 3638.50
AFRICA 9964.22 60.83 66.58 99285739.87 3700.78 4432.76
AFRICA 10095.61 69.14 73.56 101921344.66 4780.62 5410.63
AFRICA 10749.86 73.52 77.57 115559472.12 5405.04 6017.73
AFRICA 11954.36 72.64 78.06 142906752.17 5277.15 6092.58
AFRICA 12362.58 58.46 65.58 152833478.55 3417.34 4301.26
AFRICA 13724.72 74.67 77.10 188368044.84 5575.16 5944.87
AFRICA 15356.46 62.94 68.71 235820790.55 3960.81 4720.79
AFRICA 16836.61 64.16 67.28 283471298.43 4116.63 4527.14
AFRICA 18864.11 71.08 77.79 355854482.45 5052.37 6051.28
AFRICA 25524.96 68.40 78.30 651523327.91 4678.56 6130.89
AFRICA 27572.59 56.14 58.94 760247581.82 3152.15 3474.04
TOTAL 278173.52 3002.40 3181.53 3505788848.24 185779.00
208784.
11
AFRICA 2015/GDP(in
$)X
MALE/LIFE EXPECTANCY
(Y)
FEMALE/LIFE
EXPECTANCY (Z)
sum 278173.52 3002.40 3181.53
square 3505788848.24 185779.00 208784.11
n 49 49 49
SD 6270.43 6.08 6.72
Table 11: Asia data calculations
CONTINEN
T 2015/GDP(in $) MALE/LIFE
EXPECTANCY
FEMALE/LIFE
EXPECTANCY X-SQUARE Y-SQUARE Z-SQUARE
ASIA 1809.02 62.05 64.61 3272540.65 3849.71 4174.84
ASIA 3132.57 70.59 73.94 9812979.39 4982.38 5466.98
ASIA 7743.34 69.59 70.03 59959283.32 4843.05 4904.62
ASIA 74600.16 75.46 78.76 5565184513.17 5693.76 6202.67
ASIA 748.42 55.14 59.09 560125.42 3040.75 3491.86
ASIA 3290.95 66.47 70.57 10830368.05 4418.79 4980.12
ASIA 13569.89 74.64 77.67 184141956.05 5571.28 6032.16
ASIA 53595.24 81.40 87.30 2872450266.72 6625.96 7621.29
ASIA 5754.06 66.86 69.88 33109259.38 4469.86 4883.49
ASIA 10367.70 67.00 71.18 107489105.78 4489.54 5065.88
ASIA 16500.90 74.67 76.87 272279717.72 5575.31 5909.15
ASIA 37818.09 80.79 87.05 1430207988.97 6527.02 7577.70
ASIA 34177.65 78.99 85.48 1168112065.09 6239.42 7306.83
ASIA 5755.06 64.81 67.84 33120709.91 4199.82 4601.72

ASIA 100444.56 80.71 86.62 10089109456.02 6514.27 7503.54
ASIA 25001.61 73.01 77.54 625080636.26 5330.17 6012.92
ASIA 13705.01 76.11 78.18 187827170.86 5792.88 6112.11
ASIA 11411.94 65.09 73.34 130232422.63 4236.84 5379.05
ASIA 2314.27 68.32 71.49 5355868.22 4668.17 5111.25
ASIA 4695.70 65.38 67.33 22049597.35 4274.41 4533.73
ASIA 6874.58 65.68 72.50 47259885.45 4314.39 5256.54
ASIA 80892.06 80.40 84.90 6543526153.79 6464.16 7208.01
ASIA 11196.40 71.71 78.44 125359302.85 5141.89 6152.05
ASIA 15236.71 71.37 78.95 232157223.89 5093.39 6233.58
ASIA 5554.86 71.30 80.71 30856448.02 5083.55 6514.59
ASIA 43926.47 75.93 77.84 1929535121.26 5765.82 6059.69
ASIA 30549.10 78.15 82.54 933247570.06 6107.89 6812.19
ASIA 14928.89 67.48 71.90 222871649.01 4553.42 5169.32
ASIA 32024.35 80.10 84.10 1025559170.37 6416.01 7072.81
ASIA 8491.05 72.53 75.93 72097935.38 5260.89 5765.82
ASIA 68476.33 73.70 75.85 4689007091.06 5431.69 5752.62
ASIA 13352.71 77.79 81.29 178294954.96 6050.97 6608.71
ASIA 40138.95 75.08 79.27 1611135445.56 5636.26 6283.89
ASIA 119749.43 77.25 79.74 14339925634.74 5967.72 6357.67
ASIA 50723.71 73.11 76.11 2572895024.50 5345.66 5792.43
ASIA 23388.48 72.23 78.74 547021057.61 5217.32 6200.30
ASIA 65975.38 76.41 78.61 4352750178.55 5839.10 6179.22
ASIA 2641.05 63.33 66.19 6975123.07 4011.07 4380.85
Total 1060556.66 2740.64 2898.39 62270661001.11
199044.5
7 222672.22
AFRICA 2015/GDP(in $)X
MALE/LIFE
EXPECTANCY
(Y)
FEMALE/LIFE
EXPECTANCY
(Z)
sum 1060556.66 2740.64 2898.39
square 62270661001.11 199044.57 222672.22
n 38.00 38.00 38.00
SD 29321.80 6.03 6.49
MEAN 27909.39 72.12 76.27
Table 12: Europe data calculations
CONTINENT 2015/GDP(in $) MALE/LIFE
EXPECTANCY
FEMALE/LIFE
EXPECTANCY X-SQUARE Y-SQUARE Z-SQUARE
EUROPE 17000.17 71.10 78.00 289005686.43 5055.21 6084.00

EUROPE 20545.08 71.40 78.70 422100194.77 5097.96 6193.69
EUROPE 25034.45 72.40 79.70 626723723.39 5241.76 6352.09
EUROPE 13277.80 73.00 78.10 176299975.96 5329.00 6099.61
EUROPE 12759.82 73.56 77.59 162812919.72 5410.63 6020.21
EUROPE 28308.88 73.70 80.90 801392673.82 5431.69 6544.81
EUROPE 10932.05 74.17 79.23 119509688.98 5501.49 6277.71
EUROPE 20759.05 74.30 80.40 430938079.94 5520.49 6464.16
EUROPE 25299.97 74.40 82.20 640088702.03 5535.36 6756.84
EUROPE 10971.29 76.21 80.30 120369259.50 5807.81 6447.61
EUROPE 30605.42 76.40 82.70 936691765.28 5836.96 6839.29
EUROPE 29037.74 78.20 84.10 843190441.62 6115.24 7072.81
EUROPE 26607.83 78.40 84.80 707976783.52 6146.56 7191.04
EUROPE 43937.95 78.70 83.60 1930543198.15 6193.69 6988.96
EUROPE 38885.90 78.80 84.10 1512112888.96 6209.44 7072.81
EUROPE 41722.92 78.80 83.90 1740802208.82 6209.44 7039.21
EUROPE 24170.30 79.10 84.20 584203490.89 6256.81 7089.64
EUROPE 45458.70 79.10 83.20 2066493146.47 6256.81 6922.24
EUROPE 94088.59 79.40 85.20 8852663186.89 6304.36 7259.04
EUROPE 37765.75 79.50 86.00 1426251938.69 6320.25 7396.00
EUROPE 44288.93 79.60 84.20 1961509209.46 6336.16 7089.64
EUROPE 61543.21 79.60 83.50 3787566118.08 6336.16 6972.25
EUROPE 34272.75 79.80 84.20 1174621286.30 6368.04 7089.64
EUROPE 38839.17 79.80 83.50 1508480889.90 6368.04 6972.25
EUROPE 46494.36 80.00 83.50 2161725907.74 6400.00 6972.25
EUROPE 64008.29 80.10 84.20 4097060782.96 6416.01 7089.64
EUROPE 32291.16 80.60 86.30 1042718704.11 6496.36 7447.69
EUROPE 45679.28 80.60 84.60 2086596438.36 6496.36 7157.16
EUROPE 34317.57 81.10 86.00 1177695738.50 6577.21 7396.00
EUROPE 57264.16 81.10 85.40 3279183722.40 6577.21 7293.16
EUROPE 42674.42 81.30 84.50 1821106464.01 6609.69 7140.25
Total 1098842.94 2404.24 2566.82 48488435215.66 186762.20 212731.70
AFRICA 2015/GDP(in $)X
MALE/LIFE
EXPECTANCY
(Y)
FEMALE/LIFE
EXPECTANCY
(Z)
sum 1098842.94 2404.24 2566.82
square 48488435215.66 186762.20 212731.70
n 31 31 31
SD 17540.96 3.11 2.52
MEAN 35446.55 77.56 82.80