## Possible answers for the free response question on Test 1, Spring 2026

# 6 pts
#(a)
ga <- ggplot(data = moviedata, aes(y = Audience_rating, x = Critics_rating))
ga + 
  geom_point(aes(color = Rating)) + 
  facet_wrap(~Format, nrow = 1) 

ga <- ggplot(data = moviedata, aes(y = Audience_rating, x = Critics_rating,color = Rating))
ga + 
  geom_point() + 
  facet_wrap(~Format) 

# 5 pts
#(b)
gb <- ggplot(data = moviedata, aes(x = Duration))
gb + geom_histogram(bins = 12) + labs(x = "Movie Duration")
 
# 6 pts
#(c)
moviesmall <- moviedata %>%
filter(Year >= 2000) %>%
select(IMDB_ID, Audience_rating, Critics_rating, Format) %>%
mutate(total_rating = Audience_rating + Critics_rating)

# 6 pts
#(d)
moviedata %>%
group_by(Rating) %>%
summarize(
N=n(),
MeanAudRating = mean(Audience_rating)
) %>%
arrange(desc(MeanAudRating))

# 6 rows, for the 6 rating types.


# 3 pts
#(e)
Combined <- moviedata %>%
inner_join(MovieRevenues, by=c("IMDB_ID"="IMDB_ID"))

# or:

Combined <- moviedata %>%
inner_join(MovieRevenues, join_by("IMDB_ID"))