stats final project Essay

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Words: 1172
Pages: 5
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Determinants of Life Expectancy
STERN STAT-UB.0103.02

Executive Summary

Average worldwide life expectancy has significantly increased over the past century due to scientific innovation, life-saving medical discoveries, and globalization. Despite our ability to fly to any part of the globe within a matter of hours, stark differences in life expectancy continue to exist between borders. Our research aimed to uncover some major determinants of life expectancy, and the extent of their positive or negative impact. A nation’s GDP per capita, AIDS rate, and its number of physicians per 10,000 people impact life expectancy. Whether or not a country has an electoral democracy is not statistically significant at a 95% confidence level. In doing our study, we randomly selected 50 nations, compiled data for each nation, and ran multiple regressions, as well as histograms and scatterplots to determine the interrelationships and normality of the data. After a few transformations described within the report, we came up with this model for describing the relationship between life expectancy and our 3 variables:

ln(life expectancy)= 3.84 + 0.0186 ln(physicians per 10,000 people) + .0455 ln(GDP per Capita) -0.0112 (Aids Rate)

This model could be useful to determine how to improve life expectancy, and by how much life expectancy is expected to improve.

Table of Contents

Original Data Set………………………………………………………………3
Histograms of Each Variable…………………………………………………..4-5
Scatterplots……………………………………………………………………..6-7
First Regression Sketch………………………………………………………...8-9
Regression Sketch with Transformations……………………………………....9-10
Regression Sketch Excluding “Electoral Democracy”………………………...11-12
Standardized Residuals against Fitted Data……………………………………12
Final interpretation of data……………………………………………………..13
Citations…..………………………………………………………………………………………..….14

OUR ORIGINAL SET OF DATA

50 Countries
(Randomly Selected)
Life Expectancy
(Dependent Variable)
GDP per Capita (millions)
Electoral Democracy
Aids Rate
Physicians per 10,000 people
(Rounded)
Andorra
82
41517
1
0.10
39.0
Argentina
76
11452
1
0.10
32.0
Armenia
71
3338
0
0.10
29.0
Bahamas
75
21908
0
2.80
28.0
Barbados
78
14917
0
0.90
18.0
Belarus
71
6685
0
0.40
38.0
BruneiDarussalam
77
41127
0
0.10
14.0
Bulgaria
74
6986
0
0.10
38.0
Cape Verde
72
3838
1
0.10
3.0
Colombia
78
7752
0
0.50
15.0
Croatia
77
13227
1
0.05
27.0
Cuba
78
5382
0
0.20
67.0
Dominica
74
6691
0
0.70
0.0
Dubai
77
16350
0
0.10
0.0
Ecuador
76
5425
0
0.40
17.0
El Salvador
72
3790
1
0.60
16.0
UnitedKingdom
80
38514
0
0.30
28.0
Estonia
76
16316
1
1.30
33.0
Ethiopia
60
470
0
1.40
0.3
France
82
39771
1
0.40
33.8
Gambia
58
512
0
1.50
1.1
Germany
81
41514
1
0.10
36.9
Haiti
63
770
0
1.80
0.0
Ireland
81
45835
1
0.30
31.0
Kenya
60
862
0
6.20
1.8
Kyrgyzstan
69
1159
0
0.40
24.7
Laos
68
1399
0
0.30
1.9
Lesotho
50
1193
1
23.30
1.0
Lithuania
74
14150
1
0.10
36.4
Macau
81
78275
0
0.10
0.0
Mauritania
59
1106
0
1.10
1.3
Nauru
71
5000
0
0.20
7.1
New Zealand
81
31999
1
0.10
27.4
North Korea
69
1800
0
0.10
33.0
Oman
72
23731
0
0.10
20.5
Peru
77
6573
1
0.40
9.2
Philippines
69
2587
0
0.05
12.0
Puerto Rico
79
27677
0
0.10
0.0
Russia
69
14037
0
1.10
43.1
Serbia
74
5189
1
0.10
21.1
Seychelles
74
11758
0
0.10
15.0
Slovakia
76
16934
1
0.05
30.0
Spain
82
29195
1
0.40
39.6
Sri Lanka
75
2923
0
0.05
4.9
Suriname
72
8864
0
2.40
5.0
Trinidad
71
17934
0
1.50
12.0
USA
79
49965
1
0.60
24.2
Ghana
64
1604
1
0.05
0.9
Japan
83
46720
1
1.50
21.4
Italy
82
33049
1
0.40
38.0

Histograms of Each Variable to Assess Normality and Detect Possible Outliers
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