R in Rstudio

Data set olympic_running (available from tsibbledata package: install if necessary) contains the winning times (in seconds) in each Olympic Games sprint (Length=100 meters), middle-distance (Length=200 meters) and long-distance (Length=400 meters) track events from 1896 to 2016.

1. Plot the winning time against the year for for Sprint (100 meter) and long-distance (400 meters) events separately. Describe the main features of the plots.
2. Fit a linear and a piecewise regression lines to the data for each event [code is available in the Marathon example]. Obviously the winning times have been decreasing, but at what average rate per year?
3. Predict the winning time for each race in the 2020 Olympics. Give a prediction interval for your forecasts. What assumptions have you made in these calculations? Cross check your prediction with actual result from Olympic records of 2021 Tokyo (posponed due to Covid from 2020).