Part 1 Choose an airport (preferably in a city with one major airport) and find data online for annual passenger number for at least 20 years (until 2019). Also get yearly

data for those years on income per capita (or GDP per capita) and population of the city that the airport serves. Sometimes, if income per capita for the city is not available every year, use national/state income per capita. You may have to do a linear interpolation for population. If you think you need other variables to explain the evolution of air transport demand, collect those as well. a) Create a table with the collected data, mention clearly your data source. Put this table in your main assignment answer sheet. You need to also upload an excel datasheet in the second submission area in Minerva [so that I can run your model myself and check]. b) Plot the variables collected against time. Plot each variable in a separate figure. c) Derive two forecasting models (i and ii below) using the data collected: i. Demand = f(year) linear model ii. Per capita demand = f(income per capita, other variables) - all continuous variables in logarithm iii. Which of those models will you choose for forecasting passenger no in your chosen airport? Why? (max 100 word) d) Using c-ii above, forecast the number of total passengers in 2025. [Find predicted population, income growth using online sources - make sure you cite the sources].