Please Indicate

  • Who you collaborated with: Zach Levitt, Jack Kajan
  • Approximately how much time did you spend on this problem set:90 minutes
  • What, if anything, gave you the most trouble: Figuring out how to find the correct code for what I wanted to graph. I had to go back to the text book alot and see what the examples there showed and how I could apply that to this data.

Question 1: Movie Ratings- Relationship Between Comedies and Noncomedies

Within these 1000 movies, there is not significantly higher ratings for comedies than their is for non comdies. In the scatter plot there is about an equal amount of comdies and non comdies throught the graph (both with high and low ratings), meaning that both comdies do not get a higher rating than noncomdies with these 1000 movies.

Question 2: Babynames- Casey

The name Casey for both make and female followed a similar trend, of increasing steadily around the 1980s, peaking, then steadily decreasing in the late 1990s/2000s. Given that the the name Casey can be used for the both male and female this unique trend of both genders following a similar path could show the progress of gender equality during the 1980s, the progress being that it was okay for females to have the same name as males and vise versa. Before the 1960s, having names that weren’t gender binary were not common, maybe due to the strict gender roles and barriers yet as gender equality began to progress having gender neutral names became more common and accepted, like the name Casey. The name Casey in particular seams to be more common throughout both males and females because it has neither a overtly masculine sound or feminine sound, like how Julia sounds overtly feminine, while the name Mark sounds more masculine.