To predict sales for day 60, substitute 60 into the given regression equation, resulting in a forecast of $250,120. For day 90, a similar substitution gives a forecast of $324,520.
To compute the forecast for the first quarter of year 4 using linear regression, which includes the trend and quarter seasonal effects, we can rely on the provided regression equation ŷ = 101.32 + 2.48x, where x represents the day and ŷ the sales in thousands of dollars. However, the information provided does not include explicit seasonal adjustments; thus, we will use the given trend equation as is for prediction.
For day 60, the predicted sales are calculated by substituting x with 60 in the given equation: ŷ = 101.32 + (2.48 * 60). This results in ŷ = 101.32 + 148.8 = 250.12, or $250,120 when converted from thousands of dollars.
For day 90, using the same approach: ŷ = 101.32 + (2.48 * 90) = 101.32 + 223.2 = 324.52, or $324,520.