The Consumption Function - Re-Modelled Using Logarithmic Regression

Abstract: The conventional linear consumption function was compared to a proposed logarithmic consumption function using collected data as the basis for studying the accuracy of each function. To kick things off, the current linear model was studied in full to lay the groundwork for sound comparison. Following after, the data collected from survey respondents was presented along with an assimilation to fit the data points in the form of the variables used in the study. Then, using the data points presented, two curves – a linear consumption function and a logarithmic consumption function were developed using regression and technology. The next step of the process was to estimate the goodness of fit for each function against the real data collected. Results concluded that the logarithmic model was 36.6% more accurate than its linear counterpart. For the logarithmic model to stand, it needs to abide by certain properties of the consumption function, i.e, the requirement for the derivative to lie between 0 and 1, and the existence of a finite multiplier effect. The validity of these two properties were tested in the logarithmic model, both of which proved to be true, thus concluding the investigation – the logarithmic model is a viable alternative as it meets all the properties, and it is far more accurate than the linear model. The applications of the study were then discussed following an elaborate conclusion, that explored the limitations of the experiment and ways to improve it should it be conducted again at a later point of time.

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The Hyperinflated Faith in Our Understanding

Summary: Data wields the capability to reshape our comprehension of the world, laying the groundwork for decisions by both individuals and governments. Despite its vast potential, the prevalent trend is to deploy data in substantiating established convictions, cherry-picking evidence that fits within the confines of our pre-set views. This method is ingrained in our academic fabric, where argumentative essays are often appraised on the adept isolation of corroborative data, not on critical engagement with diverse perspectives. Such a practice is mirrored in political dialogues, where data is marshaled not as a beacon of enlightenment but as an instrument of affirmation. Challenging this norm requires a rekindling of curiosity, a willingness to let data lead us to impartial discoveries and to see beyond the veil of our entrenched narratives.

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The villainization of disagreement

Summary: In our contemporary discourse, we often witness an aversion to integrating diverse perspectives, particularly those that unsettle the familiar currents of thought that have long dictated societal norms. This reluctance to engage with differing viewpoints, especially from individuals of varied backgrounds, undermines the very concept of a pluralistic society. However, places of learning like UCLA are beginning to pivot towards a more inclusive approach, recognizing that a multiplicity of ideas is the bedrock of intellectual and cultural growth. By actively promoting a dialogue that encompasses the full spectrum of human experience, the university is taking promising steps in the right direction. This embracement of diversity goes beyond mere tolerance; it is an active engagement with the unfamiliar, which is crucial in crafting policies and principles that resonate with the broader fabric of society. It’s a recognition that the art of disagreement is not just about confronting opposition, but about understanding the layered and shared aspirations of a diverse populace.

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