You Are In A Brainstorming Session At Widgecorp Where 662880
You Are In A Brainstorming Session At Widgecorp Where No Idea Is Too
You are in a brainstorming session at WidgeCorp, where no idea is too outrageous. You are discussing penetration in the school lunch market. Ideas around school lunch subsidies, Internet subsidies, and Internet target marketing are being discussed. As the end of the meeting, the group asks you to prove or disprove some assumptions by looking at correlations. First, acquaint yourself with the Internet subsidy issue by reading the article Closing the Digital Divide: Internet Subsidies in Public Schools by Austan D. Goolsbee and Jonathan Guryan. Next, download the file Sample Data. Based on the findings as reported in this article, prepare a chart similar to the one in the downloaded file to indicate if the correlation between Variables A and B were found to be positive, negative, or minimal. In your own words, explain what it means if the correlation of 2 variables is positive, negative, or minimal (close to 0), and give an example of each. 400–600 words APA Style Reference Goolsbee, A. D., & Guryan, J. (2003). Closing the digital divide: Internet subsidies in public schools. Capital Ideas, 5(1). Retrieved from the University of Chicago Booth School of Business Web site:
Paper For Above instruction
In the ongoing effort to bridge the digital divide and improve educational equity, internet subsidies in public schools have become a critical policy focus. The article by Goolsbee and Guryan (2003) examines the impact of such subsidies on internet access within public schools and provides valuable insights into the correlation between government spending and internet connectivity outcomes. As part of the analysis, understanding the nature of correlations between different variables related to subsidies and connectivity is essential. This essay explores the concepts of positive, negative, and minimal correlations, illustrating each with relevant examples, and interprets the findings in the context of school internet subsidies.
Correlation is a statistical measure that expresses the extent to which two variables are linearly related. The correlation coefficient, typically denoted as "r," ranges from -1 to +1. A positive correlation (values approaching +1) indicates that as one variable increases, the other tends to increase as well. For example, in the context of school internet subsidies, a positive correlation might be observed between the amount of subsidy funds allocated to a school and the percentage of students with internet access. This suggests that increased funding is associated with higher levels of internet connectivity, supporting the hypothesis that subsidies facilitate improved access.
Conversely, a negative correlation (values approaching -1) implies that as one variable increases, the other tends to decrease. An example in the education technology context could be the relationship between the number of internet restrictions implemented and student internet access. If more restrictions are applied (e.g., filters or blockages), actual accessible internet use might decline. Such a negative correlation suggests that increased restrictions could hinder internet penetration despite available subsidies, indicating a potential counterproductive policy approach.
Minimal or no correlation (values close to 0) signifies that there is no significant linear relationship between the two variables. For instance, if the level of internet subsidies does not appear to be associated with student academic performance across schools, the correlation coefficient would be near zero. This lack of correlation suggests that other factors may be more influential in determining student outcomes, and financial subsidies alone might not be sufficient to produce improvements in educational achievement.
In the context of Goolsbee and Guryan’s (2003) research, analyzing the correlation between subsidy levels and internet usage metrics helps determine whether policies are effective or if other variables need to be considered. A positive correlation supports the premise that increasing subsidies enhances internet access. A negative correlation might indicate barriers or unintended consequences, such as restrictive policies. Minimal correlation could suggest a need to explore additional factors influencing digital access and educational success, such as infrastructural quality or digital literacy levels.
By creating a chart similar to the sample provided and analyzing the correlations accordingly, policymakers and educators can better understand the dynamics at play. A visual representation clarifies relationships and guides decisions toward strategies that genuinely close the digital gap. Overall, by comprehending the implications of different correlation types, stakeholders can design more targeted interventions to ensure that internet subsidies effectively improve connectivity and educational outcomes.
References
- Goolsbee, A. D., & Guryan, J. (2003). Closing the digital divide: Internet subsidies in public schools. Capital Ideas, 5(1). Retrieved from the University of Chicago Booth School of Business Web site