time series or ruer prices for ultra-low suipnur uneaaea petrol (US and ultra-low sulphur diesel (USLD). The project is on finding good forecasts for both time series. Read the weekly data into a dataframe, say fuel. Then read the fuel prices series using library (forecast) library (lubridate) ulsp = msts (fuel [, 2], seasonal=365.25/7, start = decimal_date (as. Date("2003-06-09"))) ulsd = msts(fuel [,3], seasonal=365.25/7, start = decimal_date (as. Date("2003-06-09"))) (In your future endeavour with weekly data, you may want to remember that frequency=52 is not exactly right, but should be exactly 365/7 for non-leap years, and 366/7 for leap years, making it on average 365.25/7 as there is a leap year every 4 years) 1. Present time series plots to display the data, and other proper plots that you think is helpful to reveal the structure of the data. Describe what you found. 2. Using the knowledge you gained from part 1, find time series models to separately model the 2 different serie