1. Consider the monthly International Passenger totals (# of Pass. in 1000s) for an airline provided in the Excel file. Use Excel to perform following analysis.

1. Find the 3-month and 6-month moving averages for all data values and find all forecast and forecast for February 2024. Find MAD for both forecasts and determine the best moving average forecast.

1. Find the three-month weighted moving average forecasts and find all forecasts and forecast for February 2024 if weights of 0.2, 0.3, and 0.5 are used with highest weights assigned to the latest months. Find MAD and compare with MADs in part (a). Is the weighted MA forecast better than simple moving averages in part a?

1. Use the exponential moving average to find all forecasts and the forecast for February 2024 Assume forecast of 500 for January 2014 anda=0.70. Find MAD and compare to MAD values in parts (a and b).

1. Construct a linear trend line graph of # of Passengers (use smooth line graph option), insert the equation of the best linear fitted line and the R-squared value. Discuss findings (time series components) based on graph.

1. Find monthly seasonal relatives (indices) and construct a column of de-seasonalized values for # of Passengers by dividing monthly number of passengers by respective seasonal monthly indices.

1. Construct a trend linear line graph of De-seas # of Passengers line (use smooth line graph option), insert the best linear fitted line and R-squared. Discuss findings based on graph, equation, and R². Is this model a better fit compared to model in part (d). Explain why?

1. Use the linear trend line equation model in part f to find forecasts for February to May 2024 and seasonalize forecasts by multiplying by respective monthly seasonal indices obtained in part (e).