The data obtained from the calculation of correlation gives an indication at the point where the data indicate a positive one (+1), there is a perfect correlation between diabetes and arthritis resulting in a perfect linear relationship between the two chronic diseases. There is a variation however at the point where r = 0.405953967 showing that there is a weak but upward linear relationship between diabetes and arthritis (Cohen, 2014).
Interpretation of the chi-square test results for association between diabetes and arthritis
In chi square test, we look for the p-value. The value provides the likelihood a sample statistic being observed as extreme as the statistic test. In this case, we will calculate the degree of freedom. The hypothesis in this case is that if a doctor has ever told a person if he or she has ever had diabetes or arthritis. The other hypothesis is that, if a doctor has never told a person that they have diabetes or arthritis. In order to analyse this case, the significance level is 0.05 and then use the sample information to carry out the chi square test for independence.
Delegate your assignment to our experts and they will do the rest.
In the sample data analysis, there is the computation of the degrees of freedom using the chi square test for independence and this involves the computation of expected frequencies. In this case, the calculation is computed on the excel sheet and the result was 0.00000000 140136. The interpretation of this is that since it is less than the significance level of 0.05, we cannot accept the null hypothesis. Therefore, the conclusion is that there is a relationship between diabetes and arthritis (Singhal & Rana, 2015).
References
Cohen, P. (2014). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. doi:10.4324/9781410606266
Singhal, R., & Rana, R. (2015). Chi-square test and its application in hypothesis testing. Journal of the Practice of Cardiovascular Sciences , 1 (1), 69. doi:10.4103/2395-5414.157577
