1 Analyze the distribution of `departure delays`. Use the space below for your graphical and numerical analysis. - Store the summary of this variable in Q1. - Your output should look something like this: ``` Min. 1st Qu. Median Mean 3rd Qu. Max. NA's [value] [value] [value] [value] [value] [value] [value] flights %>% ggplot(aes(x=dep_delay))+ geom_histogram(binwidth = 10, fill = "blue", color = "yellow", alpha = 0.7) + labs(title = "Distribution of Departure Delays", x = "Departure Dealy (minutes)", y = "Frequency") + theme_minimal() # Numerical summary of the 'departure_dealy' Q1 <- flights %>% summarise( Min = min(dep_delay, na.rm = TRUE), `1st Qu.` = quantile(dep_delay, 0.25, na.rm = TRUE), Median = median(dep_delay, na.rm = TRUE), Mean = mean(dep_delay, na.rm = TRUE), `3rd Qu.` = quantile(dep_delay, 0.75, na.rm = TRUE), Max = max(dep_delay, na.rm = TRUE), `NA'S` = sum(is.na(dep_delay)) ) Q1 <- as.data.frame(Q1) it didn't work. The expected answer is : summaryDefault, but my answer is came data.frame why this happened