美国大学论文代写：人口比率研究
美国大学论文代写：人口比率研究
从本文的分析中可以看出，研究使用了已经收集到的数据。使用次要数据来源形成结论。研究人员自己收集世界人口信息是不可能的。需要从不同的数据库收集资源和数据。因此，所收集的数据不是主要的数据来源。然而，对结果的分析和解释却与其他研究理论截然不同。人口比率和绝对数量与其他研究结果是不同的。世界人口以两种主要意识形态为基础。它是基于社会的预期寿命和未来的生育率。这在不同的大陆之间是不同的。这是一种基于贝叶斯概率法的统计分析方法。它不考虑过程中涉及的许多不确定因素。这项统计分析确定，到2100年，非洲人口预计将从今天的10亿增至40亿，增加四倍。
美国大学论文代写：人口比率研究
非洲人口到2100年有80%的统计机会从35亿增长到51亿。亚洲有44亿人口，预计2050年将达到50亿。由此可以预测，人口数量将开始下降。其他大陆的人口预计将保持在10亿以下。这些数据与联合国2013年的预测相反。研究人员称，在这项研究中，数据的准确性更高。它提供统计驱动的评估，使预测更容易量化。这也提供了更多的确定性(Gerland et al.， 2014)。利用这些数据结果，建议人们可以据此制定计划。除这些发现外，还发现它们缩小了研究范围和统计不确定度的发现。这导致人们形成了一种更健壮的方法来确定结果。
美国大学论文代写：人口比率研究
For the purpose of this analysis it can be seen that the researches had used data that was already collected. Secondary source of data was used to form conclusions. It is not possible for the researchers to collect world population information by themselves. There is a need for collection of resources and data from different data banks. Owing to this reason data that has been collected was not primary source of data. Nevertheless the analysis and the interpretations of the results are starkly different from other research theories. Rate of population and the sheer volume of numbers are found to be different from the other research findings for the same. World population is based on two primary ideologies. It is based on life expectancy and future fertility rates in the societies. This is found to vary between different continents. This is a statistical analysis that is based on Bayesian probabilistic method. It does not factor in many uncertainties involved in the process. This statistical analysis determines that in Africa population is projected to quadruple from 1 billion today to 4 billion by 2100.
美国大学论文代写：人口比率研究
There is an 80% statistical chance that population in Africa towards 2100 will grow from 3.5 billion to 5.1 billion people. Asia has 4.4 billion populations it is expected to reach 5 billion people in 2050. From this there is a projection that the population will start to decline. Populations in other continents are expected to stay below 1 billion. These figures are in lieu with U.N. projections from 2013 in this work the researchers claim there is more veracity. It provides statistically driven assessment that allows easier quantification of the prediction. It also offers more certainty (Gerland et al., 2014). Using these data findings it is suggested that the people can plan accordingly. Apart from these findings it was found that they have narrowed the scope and statistical uncertainty findings. This has led to people forming a more robust approach to determine the results.
