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A curious phenomenon was observed in 2013: despite global warming predictions, the average temperatures had not risen for about a decade. This A exercise presents two sets of the most reputable sources of global temperature data, one from the United Kingdom’s Met Office and another one from the United States’ National Aeronautics and Space Administration (NASA); students are tasked with investigating the global warming “plateau” from a statistical perspective. Does the data support that temperatures have been rising over the last 150+ years, and if so, what could explain the observed plateau? The exercise is open-ended—it provides the data and references to some popular press articles on the subject of “plateau” but leaves it up to students to figure out how to analyze the data. Also available in this set is a B exercise that presents three sets of analysis typical for MBA students—an efficient starting point for class discussion.
A case objectives: • To strengthen students’ ability to analyze time-series data and the key concepts of such analysis: random walks, trends versus cycles, Holt’s and Winter’s exponential smoothing models, runs tests, and autocorrelations • To reinforce the notion of statistical significance • To reinforce assumptions underlying linear regression and hypothesis testing B case objectives: • To be able to select, from a set of potential methodologies, the one that is most appropriate for the analytical task at hand • To be able to critically examine the presented analyses of others and use the identified “mistakes” to guide in creating a better analytical approach