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Analysis and modeling of child mortality.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.).
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
2014 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Child mortality has always been a strong indicator on the general wealth of a country therefore was decreasing it in the world one of the millennium goals. Since child mortality is such an important measure we have decided to make a structural model of it. This is an investigation regarding the causes of child mortality.

The definition of child mortality is the number of children that died before the age of five. Not to be mixed with infant mortality which is a measure of those who died before the age of one. In contrast to infant mortality we think that child mortality strongly depends on other factors than just sickness, that’s why we chose to investigate child mortality among the two of them.

We emanated from the assumption that it was possible to describe child mortality with the model:



With that in mind we collected data from the UN and the World Bank for child mortality and all possible factors that could affect child mortality.

The analysis is made with the method "multiple linear regression". At the end it all came down to a structural model consisting of six explanatory variables which are:

• U-nation

• GNI in PPP-terms

• Improved sanitation

• Average precipitation

• Help organization

• Colony

All of these variables got a positive coefficient in their effect on child mortality except for "GNI in PPP-terms" and "improved sanitation" which rationally got a negative sign. We also made a model which could be used for predicting child mortality. The difference between the prediction model and the structural model is the variable birthrate which is included in the prediction model but not in the structural model. In the prediction model birthrate got a positive sign.

Place, publisher, year, edition, pages
2014. , 32 p.
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-148956OAI: diva2:737906
Available from: 2014-08-14 Created: 2014-08-14 Last updated: 2014-08-14Bibliographically approved

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