#Correlation value is -.063, this shows little to no linear relationship between Year Num: representing the year of the data, and Stub_label_Num which represents a categorical demographics. #This slightly negative correlation doesnt indicate a reliable relatinship. If it was more negative value it might imply as the year increases, the values in Stub_Lable_Num decreases. #Pearson Correlation method was used here because both Year Num and Stub Label Num appear to be numeric and Pearson's method is designed to measure linear realtionships between two continuous numeric variables. Pearson offers the best results for linear relationship data between two variables. ////////////// #The correlation is .325 suggesting a moderate positive linear relationship between age AGE NUM and the death rate estimate ESTIMATE #This moderate postive correlation means that as age increases the death rate estimate also tends to increase. However, this is not very strong, it indicates that older age groups to have higher suicide death rates #Pearson was used because both variables are numeric variables and the goal was to measure the strength of the linear relationship between them.

I was unable to get the plots to display. I have the code down but there something I am missing. Please advise when you have a moment. Thank you.