Respond to this post by providing suggestions for either A) Identify the dependent and independent variables in the pair. B) Identify what kind of statistical testing method should be used on the variable they choose.

A) Dependent and Independent Variables: I concur with your assessment. In this analysis, the dependent variable is the total number of deaths, as it is the outcome that we are interested in predicting or explaining. The independent variable, on the other hand, is the total number of vaccinations, as it is presumed to influence the outcome. When you posit that higher vaccination rates might lead to fewer COVID-19 related deaths, you're suggesting a causal relationship where the vaccination rate (independent variable) impacts the death rate (dependent variable). B) Statistical Testing Method: Pearson's correlation coefficient is indeed a good choice for assessing the linear relationship between two continuous variables. Since the total number of deaths is technically discrete (since you can't have half a death), it's often treated as continuous in large datasets, making Pearson's appropriate in this case