if quarter $3,0$ otherwise.

hat$(Y)=$

Based only on the seasonal effects in the data, compute estimates of quarterly sales $($in $$1,000$ s$)$ for year $6.$

$\backslash$table$[[$quarter $1$ forecast,$$,$ thousand$],[$quarter $2$ forecast,$$,$thousand$],[$quarter $3$ forecast,$$,$thousand$],[$quarter $4$ forecast,$$,$thousand$]]$

an estimated regression equation for the time series data $($in $$1,000s)$ to account for seasonal effects and any linear trend in the time series. $($Round your numerical values to one decimal place.$)$

hat$(Y{)}_t=$

Based upon the seasonal effects in the data and linear trend, compute estimates of quarterly sales $($in $$1,000$ s$)$ for year $6.($Round your answers to the nearest thousand dollars.$)$

$\backslash$table$[[$quarter $1$ forecast,$$,$thousand$],[$quarter $2$ forecast,$$,$thousand$],[$quarter $3$ forecast,$$,$thousand$],[$quarter $4$ forecast,$$,$ thousand$]]$$$1,074,000$ in the most recent year. The following data show the quarterly sales revenue in thousands of dollars.

$\backslash$table$[[$Quarter$,$Year $1,$Year $2,$Year $3,$Year $4,$Year $5],[1,20,37,75,92,176],[2,95,131,150,197,277],[3,170,240,321,379,440],[4,8,21,43,77,181]]$