Question.3908 - This week, we are learning about correlation and the Pearson r correlation coefficient. Correlations tell us about relationships between variables (not cause and effect). After you read the chapter and review the material in this module, do the following activity: Go to Google Scholar (type "Google Scholar" in Google and click the Google Scholar link that shows up as the first link). This site lets you find scholarly articles (articles published in peer reviewed journals - reviewed by peer experts, which makes them more scientifically reliable). Type "correlation between" in the search field, and a few topics will pop up as options you can choose from. Scroll through the topics and select one that sounds interesting to you, and click search or enter. Articles related to what you chose should come up. Scroll through the articles, and choose one available in PDF format ("PDF" should be noted on the right side of the article listing when PDFs are available) in the topic you have selected. Skim through the article and provide the following as best you can based on material covered in this module (do your best with what you read and understand from the article): What were the variables being explored in this study, what relationship was explored (usually in the introduction section)? What were the hypotheses in this study? What predictions were the researchers making? (usually found after the review of the literature and right before the method section) Under the results section, find a report of a correlation and type it in here (find r reported in APA style as per your textbook; any r result reported): What does this result mean? What was a decision made about this result in terms of significance? Also, what was the p value for the r you reported in question 3; is that significant or not?
Answer Below:
The study primarily explored the relationship between education level and income distribution. Variables such as years of schooling, income variance, average income, and other socioeconomic factors were analyzed to understand their impact on income distribution in the United States, Canada, and the Netherlands ( Tinbergen, 1972 ). The hypothesis was that education plays a significant role in determining income distribution ( Tinbergen, 1972 ). The researchers predicted that higher levels of education and a more equal distribution of education would help reduce income inequality. In case A, R = 0.96 for the Netherlands In the case of B, R = 0.94 for the United States In case C, R = 0.92 for the Netherlands ( provinces ) In the case of R = 0.91 for the Netherlands (municipalities) In case E, R = of0.89 for the Netherlands (provinces) In case F, R = 0.86 for Canada (provinces) .All the cases have a strong positive correlation since the R-value for all the cases is closer to 1. It suggests that the other variable will also increase as one variable increases as education increases. Income level increases. Since all the correlations (r) are quite high (close to or above 0.85), it’s very likely that these results are statistically significant, meaning the relationships between the variables are not due to random chance. There was no p- value given. References Tinbergen, J. (1972). The impact of education on income distribution. Review of Income and wealth, 18(3), 255-265.More Articles From Statistics
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