Y3_o passeu: g Question 4. Assign boston_under_15 and manila_under_15 to the percentage of rides that are less than 15 minutes in their respective metropolitan areas. Use the height variables provided below in order to compute the percentages. Your solution should only use height variables, numbers, and mathematical operations. You should not access the tables boston and manila in any way. (4 Points) Note: that the height variables (i.e. boston_under_5 ) represent the height of the bin it describes. [164]: | boston_under_5 bin_height = 1.2 b & F manila_under_5_bin_height = 0.6 boston_5_te_under_1@_bin_height = 3.2 manila_5_to_under_18_bin_height = 1.4 boston_10_to_under_15_bin_height = 4.9 manila_1@_to_under_15_bin_height = 2.2 boston_under_15 manila_under_15 boston_under_15, manila_under_15 l [164]: (Ellipsis, Ellipsis) grader.check("g3_4") q3_4 results: g3_4 - 1lresult: X Test case failed Question 5. Let's take a closer look at the distribution of ride times in Boston. Assign boston_median_bin to aninteger (1, 2, 3, or 4) that corresponds to the bin that contains the median time. (4 Points) 1. 0-8 minutes 2. 8-14 minutes 3. 14-20 minutes 4. 20-40 minutes Hint: The median of a sorted list has half of the list elements to its left, and half to its right. boston_median_bin = ... boston_median_bin grader.check("q3_5") Question 6. Identify one difference between the histograms, in terms of the statistical properties. Hint: Without performing any calculations, can you comment on the average or skew of each histogram? (4 Points) Type your answer here, replacing this text. Question 7. Why is your solution in Question 6 the case? Based on one of the following two readings, why are the distributions for Boston and Manila different? (4 Points) Boston reading + Manila reading Hint: Try thinking about external factors of the two cities that may be causing the difference! The readings provide some potential factors -- try to connect them to the ride time data. Type your answer here, replacing this text