Climate change is a current challenge that is growing faster than the measures set to calm it down. Never than before, the carbon dioxide atmospheric levels are increasingly higher. Therefore, the warming planet has resulted in droughts, floods, extreme storms, as well as intensifying sea levels. In 2015, nations across the world assumed the historic Paris Agreement on Climate change in recognition to the magnitude and urgency of the challenge aiming to regulate global average temperature rise to a value below 2 °C. Currently, the world is not on the track to obtain the Paris targets. In this case, the post has applied inductive generalization. An inductive generalization proceeds from a premise of a sample to an inference concerning the population. In this situation, the historic Paris Agreement is the sub-group that is generalized for the entire globe about the steps in limiting the global average temperature with regard to Paris Agreement (Williams & Tsang, 2016). Therefore, this case presentation is a good example of inductive generalization since it involves a sub-group, “Historic Paris Agreement” which is generalized for the entire group, “World Nations.”
The argument titled “Unprecedented 3 years of global coral bleaching, 2014 – 2017” is a good illustration of the statistical syllogisms. It demonstrates that across the tropics, the relationship between coral reefs and the ocean can allude to the relationship between rainforests to the land. The heat stress, as well as the bleaching of the coral, cuts down the symbiotic relationship between them and the algae. When this partnership is curbed, corals are likely to suffer due to starvation. The history associated coral bleaching with El Nino events that often raises the global temperature. This association is believed to have inferred the global event that coincided with 1998 El Nino which results in the generalization of the event as a statistical syllogism. A statistical syllogism presents cases where a major premise is a generalization in which the arguments attempt to draw a conclusion from that generalization (Williams et.al. 2016). This implies that what a group is like is often generalized to what a group member is like. This is a good example since the symbiotic relationship of the corals and algae is assumed that the withdrawal of algae from the association due to high temperatures will result in the suffering of the corals.
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The statistical generalization of the reports shows that there was no adequate sample size. Therefore, the reports have a biased sample. The business of sampling in statistics involves some members of the population having lower sampling probability compared to others.
Climate change is an issue that requires some special attention to address (Peters & Mayhew, 2016). The world nations should be brought inboard to establish a consensus on the universal response to climate change. On a scale of 1 to 5, the urgency of the challenge of climate change can be given a rating of 3. This is because it has a direct impact on the daily living of the people. Robert Glasser, UN Sec-general’s Special Representative for Disaster Risk Reduction, highlights that climate change raises the competition for resources hence increasing tensions and global instability. The biggest obstacle that we must overcome to curb climate change is the political and partly scientific decisions. The political leaders should pave the way for the science guidance set to address the climatic change issues (Peters & Mayhew, 2016). This can be done through finance mobilization to the guidance as well as offering a conducive environment for the ideas. For the “take action” in the future, I am currently sensitizing the world on the benefits of addressing climate change by educating and taking actions such as syntheses of information on emissions.
Indisputably, the challenges of climate change can hardly be ignored. World nations should get in line with scientific guidance to address the menace. If action is taken, for instance, by addressing emission issues, then the war can be worn. Political input is necessary for the success of this move.
References
Peters, K., & Mayhew, L. (2016). The securitization of climate change: A developmental perspective. In The Securitization of Foreign Aid (pp. 212-236). Palgrave Macmillan, London.
Williams, J. N., & Tsang, E. W. (2016). Classifying generalization: paradigm war or abuse of terminology?. In Formulating research methods for information systems (pp. 151-178). Palgrave Macmillan, London.