Hi, I am having trouble understanding how to calculate these.

The data is:

Mar-2011. 2645.6

Apr-2011. 2648.9

May-2011. 2651.2

Jun-2011. 2649.2

Jul-2011. 2677.6

Aug-2011. 2707.9

Sep-2011. 2724.9

Oct-2011. 2741.7

Nov-2011. 2732.9

Dec-2011. 2704.4J

an-2012. 2763.8

Feb-2012. 2770.3

Mar-2012. 2813.1

Apr-2012. 2832.1

May-2012. 2876.7

Jun-2012. 2910.3

Jul-2012. 2921.7

Aug-2012. 2896.1

Sep-2012. 2896.2

Oct-2012 2886.6

Nov-2012 2884.7

Dec-2012. 2868.9

Jan-2013. 2870.9

Feb-2013. 2915.6

Mar-2013. 2919.0

Apr-2013. 2919.7

May-2013. 2941.0

Jun-2013. 2970.1

Jul-2013. 2959.1

Aug-2013. 2985.9

Sep-2013. 2998.8

Oct-2013. 3074.7

Nov-2013. 3127.2

Dec-2013. 3171.0

Jan-2014. 3223.4

Feb-2014. 3217.1

Mar-2014. 3259.1

Apr-2014. 3263.6

May-2014. 3267.6

Jun-2014. 3242.3

Jul-20143. 295.3

Aug-2014. 3300.3

Sep-2014. 3325.6

Oct-2014. 3289.8

Nov-2014. 3318.7

Dec-2014. 3326.1

Jan-2015. 3390.7

Feb-2015. 3382.9

Mar-2015. 3340.8

Apr-2015. 3380.4

May-2015. 3375.3

Jun-2015. 3425.9

Jul-2015. 3417.6

Aug-2015. 3394.6

Sep-2015. 3415.8

Oct-2015. 3397.4

Nov-2015. 3429.8

Dec-2015. 3431.8

Jan-2016. 3441.0

Feb-2016. 3436.6

Mar-2016. 3464.4

Apr-2016. 3497.4

May-2016. 3498.7

Jun-2016. 3507.7

Jul-2016. 3547.6

Aug-2016. 3611.4

Sep-2016. 3632.5

Oct-2016. 3617.8

Nov-2016. 3603.2

Dec-2016. 3616.2

Jan-2017. 3639.3

Feb-2017. 3642.7

Mar-2017. 3628.4

Apr-2017. 3660.0

May-2017. 3689.1

Jun-2017. 3710.1

Jul-2017. 3700.3

Aug-2017. 3662.5

Sep-2017. 3683.0

Oct-2017 3727.2

Nov-2017. 3743.3

Dec-2017. 3741.5

Jan-2018 3737.6

Feb-2018. 3771.4

Mar-2018. 3741.3

Apr-2018. 3779.8

May-2018. 3750.9

Jun-2018. 3793.9

Jul-2013. 821.3

Aug-2018. 3853.1

Sep-2018. 3847.0

Oct-2018. 3798.2

Nov-2018. 3794.4

Dec-2018. 3844.1

Jan-2019 3859.8

Feb-2019. 3863.3

Mar-2019. 3916.0

Apr-2019. 3889.8

May-2019. 3909.4

Jun-2019. 3924.0

Jul-2019 3904.0

Aug-2019. 3889.6

Sep-2019. 3896.4

Oct-2019. 3895.2

Nov-2019. 3945.9

Dec-2019. 3909.1

Jan-2020. 3910.1

Feb-2020 3935.5

For the Seasonally-adjusted data for Cafes, Restaurants and Takeaway Food (Series ID: A3348639K) available in Table 1: Forecast the out-of-sample values for every month in the period March 2020 - February 2021 (both months inclusive) using Holt's Exponential Smoothing with the following parameters: alpha = 0.5 and beta = 0.2. For the seed of the level use the first observation, Y1. For the seed of the trend - take the difference of the first two observations (Y2 - Y1). Before you begin Exercise 1, let's check that you have the right data! The average should be 3371! Once you perform Holt's Exponential Smoothing with alpha = 0.5 and beta = 0.2, what are the following numerical values: 1. The within-sample forecast for February 2020. 2. The out-of-sample forecast for March 2020. 3. The out-of-sample forecast for February 2021. 4. The MSE. 5. The MAE. Critically think for a way to optimise alpha and beta via the MSE, and report the following values after your optimisation: 6. Alpha 7. Beta 8. The MSE 9. The out-of-sample forecast for March 2020. 10. The out-of-sample forecast for February 2021