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Wilmington University *

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7060

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Statistics

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Nov 24, 2024

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docx

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2

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Introduction The following experiment is an analysis of the data based on the study by St. Leger, et al. (1978 and described in Howell, 1995). This experiment focuses on finding the correlation between the number of physicians per 10,000 population and an adjusted infant mortality rate for 10 countries. Analysis of Research Questions Research Question 1 What is the correlation between the number of physicians per 10,000 population and the adjusted infant mortality rate for 10 countries? Null Hypothesis: There is no significant correlation between the number of physicians per 10,000 population and the adjusted infant mortality rate for 10 countries. Alternative Hypothesis: There is a significant correlation between the number of physicians per 10,000 population and the adjusted infant mortality rate for 10 countries. The appropriate test in this case is the Spearman’s Rank Correlation Coefficient. This is because the variables measured are on an ordinal scale and the alternative hypothesis suggests a linear relationship between the two. Using the Spearman’s correlation coefficient, the correlation coefficient value was calculated to be 0.662 (p = 0.041). Since the p value is less than 0.05, it is statistically significant. Thus, we reject the null hypothesis and conclude that there is a significant correlation between the number of physicians per 10,000 population and the adjusted infant mortality rate for 10 countries.
Summary The results from the experiment showed that there is a statistically significant, positive correlation between the number of physicians per 10,000 population and an adjusted infant mortality rate for 10 countries. Thus, it can be assumed that the higher the number of physicians per 10,000 population, the less likely it would be for there to be an adjusted high infant mortality rate. Further studies are still needed to confirm these findings and to understand how other physiologic and environmental factors influence the correlation. In the next chapter, the analysis of the data will continue by examining the impact of gender and age of the participants in the study. Appendix A Table 1: Correlation Results Correlations Physicians Rank Mortality Rank Physicians Rank 1.000 Mortality Rank 0.662** **. Correlation is significant at the 0.05 level (2-tailed)
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