In analyzing the state data, I raised the hypothesis that a state's electoral votes for president in the 2020 election were not independent of the legality of marijuana in the state. Since Colorado became the first state to legalize recreational weed usage in 2015, there have been a variety of states that have legalized or decriminalized the substance. Based upon on the data set and watching the news the last few years, I thought that there was likely a correlation between Democratic leanings of the state and willingness to legalize marijuana. With that in mind, I chose to use the results of the 2020 election to categorize states as either red or blue. While any single data point can be tricky in categorizing a state as red (Republican) or blue (Blue), I felt that the most recent presidential election was a better categorical choice than governorship as the personal popularity of the governor could cause a state to go against its normal voting tendencies. The results of the Chi-Square test is below: A Chi-Square test of independence was performed to see whether how the state (or DC) voted in the 2020 Presidential election was related to or independent from the legality of marijuana in the state. The analysis showed these factors are not independent [X2 (1,51) = 20.05, p< .001). For example, if these variables were unrelated, we would expect 10 states that voted blue in 2020 to have legal marijuana, but the actual count is 18. Similarly, we would have expected 16 blue states to have illegal marijuana; however, there were only 8. This demonstrates lack of indepedence in the variables tested. in 120 words give a positive response to the peer ndiscuss