mehdihemmatyar / datascienceexam

DataScienceExam

1. blu Marketing

The small city of blufield has a total number of 8,000 families. Each family lives in a house. These houses are distributed over a square shaped area of 5000 by 5000 meters by the following distribution: 1) ¼ of the houses are distributed normally (mean in center) in a 2000-by-2000 square in the center. With SD=500 meters. 2) The remaining ¾ are distributed normally (mean in center) all over the city with SD=1250 meters.

This might be a sample of what blufield may look like

Blu, as an online bank, wants to see how much people spend on transportation to a regular bank. Assume the banks are located in the following locations: A: 2000, 2500 B: 4200, 4000 C: 3500,500 D: 1000,4200 E: 700,500 When going to a bank, people choose the nearest bank available. If it is less than 500 meters away, it would cost 1 unit of money to get there, if it is less than a kilometer away it costs 3 and otherwise it costs 5 units of money to get there. Using this information, answer the following: In which areas of the city should blu focus on advertising about how using blu would decrease transportation costs more? Provide a heatmap. Where is the best location to build a new bank to minimize the transportation costs? Providing a heatmap of a measure of “goodness of location” is a plus.

2. Movie database

We have a dataset of 3000 movies from the internet movie database here. This dataset includes columns such as title, genre, budget, production companies, cast, etc. Using only the information provided in this dataset, answer the following questions. (Dataset may require cleaning first)

Which are the genres with the highest number of movies? (Note that a movie may have more than one genre) Which are the genres with the highest average revenue/budget ratio for a movie? (i.e. which genres are the most rewarding ones in terms of income for the company?) Sort the production companies by the number of movies made. (Note that a movie may have more than one production company) Provide a plot of average revenue/budget ratio in different years. (X-axis would be years and Y-axis would be the average revenue/budget ratio) Group all movies into different subgroups based on budget, revenue and popularity. (Drop the movies with budget or revenue lower than 10000, these are unknown values) Explain how you choose the number of these groups. Can you provide an explanation about each group? We have some users who like to be different and ‘swim against the current’. Find them the most weird movies in terms of runtime, budget, number of cast, etc. Feel free to improvise and combine the columns! Explain your results.