$\backslash$table$[[$Day$,$Period # Demand,trend estimate,Forecast,Forecast Error,Forecast Error$^2],[$Monday$,1,,,,],[$Tuesday$,2,,,,],[$Wednesday$,3,,,,],[$Thursday$,4,,,,],[$Friday$,5,,,,],[$Saturday$,6,,,,],[$Sunday$,7,,,,],[$Monday$,8,,,,],[$Tuesday$,9,,,,],[$Wednesday$,10,,,,],[$Thursday$,11,,,,],[$Friday$,12,,,,],[$Saturday$,13,,,,],[$Sunday$,14,,,,],[$Monday$,15,,,,],[$Tuesday$,16,,,,],[$Wednesday$,17,,,,],[$Thursday$,18,,,,],[$Friday$,19,,,,],[$Saturday$,20,,,,],[$Sunday$,21,,,,],[$Monday$,22,,,,],[$Tuesday$,23,,,,],[$Wednesday$,24,,,,],[$Thursday$,25,,,,],[$Friday$,26,,,,],[$Saturday$,27,,,,],[$Sunday$,28,,,,]]$

$(3$ points$)$

$0\mathrm{.}5$

$(4$ points$)$ Step $2$

forecasts and forecasting errors. To do so:

Initially set alpha $=0\mathrm{.}5$ and beta$*=0\mathrm{.}5$ in cells $K2$ and $L2$

After that, calculate the forecast made in period $0$ for period $1$ ;

then assume that demand for period $1$ is revealed and calculate the updated level and trend estimates for period $1$ and then calculate the forecast made in period $1$ for period $2$ ; and so on

until you calculate the forecast made in period $20$ for period $21$ and you calculated the level and trend estimates for period $21$ Put the formulas for level and trend estimates in columns $E($green cells$)$ and $F($green cells$),$ respectively, and formulas for forecast calculations in column $G($yellowish cells$)$

Once one$-$step$-$ahead forecasts are calculated for periods $1-21,$ calculate the forecast errors and squared forecast errors in columns $H($pink cells$)$ and I $($gray cells$)$ respectively

Finally, write the formula for sum of squared errors in cell $124($orange cell$)$

$(3$ points$)$ Step $3$

First, make sure that you have the demand data fixed That is$,$ you copied cells D$2$:D$22$ from 'Data Generation' sheet and pasted the values only into cells D$3$:D$23$ of this sheet

Jse Excel's Data Analysis$-->$Regression on first two$-$week's $($i$.$e$.,$ periods $1-14)$ data to create the level and trend estimates in period $0$ In doing so$,$ under Output options of the Regression window, select Output Range and select A$33$ This will give the regression summary under the data table $($see below the data Use the regression result to populate cells E$2$ and F$2($blue cells in row $2)$ Then, explain which values of the regression results you use

as level and trend estimates for period $0$ and why. $2-4$ sentences would be sufficient

Determine the optimal alpha and beta$*$ values that will minimize the sum of squared errors.

To do so$,$ go to Solver and setup the optimization problem

Do not forget to add the constraints that the parameters values should be $1$

And select GRG Nonlinear from the solving method

Report how much the sum of the squared errors changed below