accessibility to technological and educational resources of the most developed countries
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8/8/2019 Accessibility To Technological And Educational Resources Of The Most Developed Countries
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Accessibility To Technological And Educational Resources Of The Most Developed Countries
Population In Comparison With The Population Of The Least Developed Countries
Adriana Coba*
*Master of Science in International Business Development‘s candidate, University of Neuchâtel, Semester autumn of
2010.
Abstract: This report seeks to determine whether the population of the less developed countries have similar access to
certain basic resources like information and education than the most developed countries, such as: Primary School
Enrollment, Personal Computers and Internet Users .
This report seeks to determine whether the population
of the less developed countries1
have similar access tocertain basic resources like information and education
than the most developed countries2, such as:
- Primary School Enrollment3
(% net) - data takenfrom year 2001 to 2010
- Personal Computers4
(per 100 person) - data taken
from year 2003 to 2010
- Internet Users5
(per 100 person) - data taken fromyear 2007 to 2010
Because it could be assumed that everyone has access
to them, given the decreases in technology prices. Then,to develop the issue above, this report will be
developed sequentially. On the other hand, it is of note,
that the above described, could be done by graphing thedata, and verifying at a glance if the averages of each
group (less developed vs. more developed) differ ineach variable, which could be done by histograms, or
Box Plot. But, to show whether the difference is
significant, it is important to use statistical tools.
1. Hypothesis formulation
The hypothesis that we want to prove is that the
average of Personal Computers users, Internet users, aswell as people with access to basic education, is similar
in most developed countries, and least developed, asfollows:
Table 1: Hypotheses formulation
Variable H0
(Null Hypotheses)
H1
(Alternative
hypothesis)
Primary School
Enrollment
PSEMDC = PSELDC PSEMDC PSELDC
Personal Computers
users
PCUMDC = PCULDC PCUMDC PCULDC
Internet Users IUMDC = IULDC IUMDC IULDC
Where:
PSEMDC: Average primary School Enrollment for most developed countries
IUMDC: Average percentage of Internet users for most developed countries
PSELDC: Average primary School Enrollment for Least developed countries
IULDC: Average percentage of Internet users for Least developed countries
PCUMDC: Average percentage of Computers users for most developed countriesPCULDC: Average percentage of Computers users for Least developed countries
2. Method for verify the hypothesesThe statistical tool that can be used to verify thehypothesis is "Comparison of two averages,
independent samples". Not will be used paired samples,because the data that we want to compare not belong to
1 http://www.unohrlls.org/en/ldc/related/62/ (Accessed 15.11.2010)2 http://en.wikipedia.org/wiki/Developed_country (Accessed 12.11.2010)3 http://data.worldbank.org/indicator/SE.PRM.NENR (Accessed 10.11.2010)4 http://data.worldbank.org/indicator/IT.CMP.PCMP.P2 (Accessed 10.11.2010)5 http://data.worldbank.org/indicator/IT.NET.USER.P2 (Accessed 10.11.2010)
the same group, but belong to two groups: The less
developed countries and more developed countries.Then, we will compare the averages of the two groups,
for each variable, using SPSS as a tool, for a confidenceinterval of 95%.
Table 2: Characteristics of samples
Level of development N Moyenne Ecart-type
Erreur
standard
moyenne
School
enrollment,
primary (%
net)
More
developed
26 97.168 2.364997 .463814
Least
developed
35 73.057 16.780829 2.836478
Personal
computers
(per 100
people)
More
developed
26 46.622 20.570056 4.034120
Least
developed
35 1.544 2.459655 .415757
Internet
users (per
100 people)
More
developed
26 64.755 15.849847 3.108411
Leastdeveloped
35 3.555 4.168819 .704659
3. Results:
By observing the resulting averages in Table 2, it was
found that:PSEMDC: 97.168 % PCUMDC:46.622 %IUMDC: 64.755 % PSELDC: 73.053 %
PCULDC: 1.544 % IULDC: 3.555 %
Which, at first glance appears to refute our hypothesisH0 and give strength to the H1 hypothesis, but, the
statistics comparisons will be shown in the followingtable:
Table 3 : Results for comparison of the averages for each variable
Test de
Levene sur
l'égalité desvariances
Test-t pour égalité des
moyennes
F Sig.
t
ddl
Sig.
(bilatérale)
School
enroll-
ment,primary
(% net)
Hypothèse de
variances
égales
39.677 .000 7.259 59 .000
Hypothèse de
variances
inégales
8.391 35.808 .000
Personal
compu-
ters (per100
people)
Hypothèse de
variances
égales
61.625 .000 12.878 59 .000
Hypothèse de
variances
inégales
11.115 25.532 .000
Internet
users (per100
Hypothèse de
varianceségales
58.541 .000 21.903 59 .000
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people) Hypothèse de
variancesinégales
19.201 27.582 .000
According to Table 3, the Levene test indicates that thevariances are significantly different (sig <0.05)
therefore we will take the data that the hypothesis of
unequal variances. Then, taking into account that thebilateral test of comparison of averages gave a bilateral
significance of 0.000 (ie <0.05) it can be said, that thehypothesis H1 for all variables is true: the accessibility
to technological and educational resources of the more
developed countries population in comparison with thepopulation of the least developed countries are
significantly different. That, as already mentioned, canalso be shown graphically, with the comparison of the
each medians (to check, lets revise two of the three
variables):
Figure 1: Comparison of the Median for access conditions to
education and internet between least and the most developed
countries.
Data Source: WorldBank (http://data.worldbank.org/)
Elaborated: Coba
Then, to have wider panoramas of the real differencesand understand better the big difference between the
least and the most developed countries in terms of
connectivity, we typify the variable, by dividing it inranges, as is:
0%-25%: Minimum percentage of Internet users
26%-50%: Lower-middle percentage of Internet users51%-75%: middle-higher percentage of Internet users
76%-100%: Major percentage of Internet users
And for the mentioned purpose, we will use a
“contingency table” in the SPSS tool: despite the“contingency table” is usually used to compare
qualitative data, in this case it could be useful to give usa better understanding of the phenomenon and to
analyze the relation between the not-developed and the
lack of access to internet.
Table 4: Contingency table for the percentage of internet users
Level of development
TotalLeast
developed
More
developed
Usuarios
de
internet -
rangos
Internet Users
between 0-
25% of the
population
Effecti f 35 0 35
% dutotal
57.4% .0% 57.4%
Internet Users
between 26-
50% of the
population
Effectif 0 7 7
% du
total.0% 11.5% 11.5%
Internet Users
between 51-
75% of the
population
Effecti f 0 13 13
% du
total.0% 21.3% 21.3%
Internet Users
between 76-
100% of the
population
Effectif 0 6 6
% du
total.0% 9.8% 9.8%
Total
Effecti f 35 26 61
% du
total57.4% 42.6% 100.0%
Tests du Khi-deux
Valeur ddl
Significationasymptotique
(bilatérale)
Khi-deux de
Pearson
61.000 3 .000
It is noted that the value of χ 2
provides a bilateralsignificance (ie, on both sides of the variance curve) of
0,000 and (again, for a confidence interval of 95%)
because 0.000 < 0.05, then it can be conclude that if weformule a hypothesis H0 which states that the level of
internet connectivity is proportional (or is associatedwith) with the development of a country, we can say
that this H0 is true. That affirmation can be supported
by some theories: "There is no digital divide - it is aneconomic divide pure and simple: to improve access
and connectivity we have to improve the economy"6.
But it is also a "vicious circle" since, without access to
sources of information and the tools provided by theInternet, is difficult form well-trained individuals whocan move forward and improve the conditions of the
country: "You cannot improve the well-being of citizens with just telephony,"
7
Finally, it is a good idea to conclude this report, noting
the globe, in terms of Internet connectivity.
6 According to Cliff Missen Director of Iowa-based eGranary Library
http://www.scoop.co.nz/stories/WO0805/S00271.htm (Accesed 18.11.2010)7 According to Tunisia Telecom President, Ahmed Mahjoub at UN Global
Forum: http://www.scoop.co.nz/stories/WO0805/S00271.htm (Accesed
18.11.2010)
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Figure 2: Internet Users by Country, per 100 people8.
Source: www.chartsbin.com
References
- Steel, R. G. D. and Torrie, J. H., Principles and
Procedures of Statistics, New York: McGraw-Hill,1960, pp. 187, 287.
- Sachs, Jeffrey (2005). The End of Poverty: Economic Possibilities for Our Time. USA: New
York: Penguin Press. OCLC 57243168.
- Torres López, Juan (1995). Economía Política.Madrid: Editorial Civitas.
- “Analisis de datos cualitativos”:http://www.uam.es/personal_pdi/economicas/eva/pdf/tab_conting.pdf (Accessed 18.11.2010)
- “Analisis SPSS: Procedimiento Tablas deContingencia”: http://e-stadistica.bio.ucm.es/web_spss/proc_contingencia.
html (Accessed 18.11.2010)
- “Comparar medias”:http://www.ucm.es/info/dosis/Preventiva/doctorado
/TEMA10.pdf (Accessed 15.11.2010)- “Developed Country”:
http://en.wikipedia.org/wiki/Developed_country (Accessed 12.11.2010)
- Internet world map_ http://chartsbin.com/view/sop
(Accesed 15.11.2010)
- “School enrollment, primary (% net)” :http://data.worldbank.org/indicator/SE.PRM.NEN
R (Accessed 10.11.2010)- “Indicadores internacionales sobre desarrollo
humano”: http://hdr.undp.org/es/datos/mapa/ (Accessed 16.11.2010)
- “Least Developed Countries Need Low-Cost PCs”:
http://www.scoop.co.nz/stories/WO0805/S00271.h
tm (Accessed 18.11.2010)- “Personal computers (per 100 people)”
http://data.worldbank.org/indicator/IT.CMP.PCMP.P2 (Accessed 10.11.2010)
- “Personal computers (per 100 people)”:http://data.worldbank.org/indicator/IT.NET.USER.
P2 (Accessed 10.11.2010)
- “UN-OHRLLS-Least Developed countries”:
http://www.unohrlls.org/en/ldc/related/62/ (Accessed 15.11.2010)
8 http://chartsbin.com/view/sop (Accesed 15.11.2010)