QUESTION 4: Predicting Quarterly Tourist Arrivals [1+1+1+2.5+1+1+2+1+1.5+1+1+1=15 marks) The tourism industry in Australia is to some extent subject to enormous seasonal variation. The Australian Bureau of Statistics (ABS) publishes various information on tourism-related variables. The quarterly short-term inbound tourist arrival numbers to Australia for the years 2014(1)-2019(4) are recorded in file ARRIVALS.xIsx. a. Plot the time series. Does there appear to be any seasonal pattern? Measuring the seasonal effect using the moving averages: b. Calculate the four-quarter centred moving averages. c. On the same graph, plot the series and the four-quarter centred moving averages. d. Calculate the quarterly seasonal indexes. e. Calculate the seasonally adjusted series. Measuring the seasonal effect using the trend method: f. Estimate the linear trend line (from regression analysis) for the data and present the estimated trend line. Calculate the quarterly seasonal indexes, using this trend line. Calculate the seasonally adjusted series and plot the unadjusted and adjusted series. Forecast the number of inbound tourist arrivals in Australia during the four quarters in 2020- 2023. e = LULD. Updating data and comparing with the forecast Effect of the Covid-19 pandemic in 2020 and bevond: j. Collect the actual quarterly tourist arrivals data for 2020-2023 and present it in a table (source should also be provided). k. Compare the actual and predicted quarterly tourist arrivals for 2020 (Covid-19 pandemic year). l. Considering the quarterly tourist arrivals for 2021-2023, comment whether the increases are on track to reach the pre-pandemic 2019 tourists arrival levels in Australia