Wentworth Medical Center depression study
Introduction
The scope of this question must deal with the Wentworth Medical Center depression
study and its correlation between geography and measure of depression. The data is based upon
the given information 60 individuals. This is an import topic of study because it would go to
prove whether or not the depression has a direct correlation due to geography.
Upon initial analysis, there is a direct correlation between the state in which the subject lived,
and their depression level. Florida had the lowest mean of 5.55 with a standard deviation 2.139.
North Carolina had the middle mean of 7.05 with a standard deviation 2.837, and New York had
the highest mean of 8 with a standard deviation 2.2. Using our Analysis of Variance, we see that
the factor sum of square is 61.03, the degree of freedom is 2, the adjusted mean square is 30.517,
F-Value was 5.24, and P-Value of .008. The error sum of square is 331.9, the degree of freedom
is 57, and the adjusted mean square is 5.823. The total degree of freedom is 59, and the sum of
square is 392.93. According to the Boxplot above there is no overlap from any of our data points
so suggest a real middle ground for these states when compared to each other.
Methods
In order to pick the correct hypothesis test, a one-way ANOVA test was used to test the
null hypothesis. The one-way ANOVA test was selected due to the given data parameters. The
alternate hypothesis would be there was no correlation between the geography and depression
level. The Wentworth Medical Center study would have to be updated if it does not match the
null hypothesis. The level of significance used is .05. Results obtained from one-way ANOVA
test shows the P-value is .008. Since the P-value of .008 is less than the .05 level of significance,
the outcome is failure to accept the null hypothesis.
Discussion/Conclusion
Overall, there is enough evidence to reject the null hypothesis. The results were as
expected, and the Wentworth Medical Center can record this as new date for the correlation
between geography and depression levels. There was no bias located within and of the given data
points. The sample was collected appropriately according to the various states in which the
subjects resided in. Future research could take and compare updated sample sizes of all the states
or U.S. territories, by income levels, gender, and political affiliation.