In the following time series linear regression equation, t is time in quarters and y is revenue in thousands of dollars. ýt= = 443.2 - 59.51Qtr1 – 59.42Qtr2+78.87Qtr3 Interpret the regression coefficient for the Qtr2 variable. On average, revenue is $59.42 thousand less in Quarter 2 as compared to Quarter 4 each year. Quarter 2 revenue decreases by $59.42 thousand as revenue values in Quarters 1, 2, and 4 increase. Revenue decreases by $59.42 thousand on average every Quarter 2. As time increases by one quarter, revenue decreases by $59.42 thousand on average.

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In the following time series linear regression equation, this time in quarters and y is
revenue in thousands of dollars.
ýt = 443.2 - 59.51Qtr1 – 59.42Qtr2 + 78.87Qtr3
Interpret the regression coefficient for the Qtr2 variable.
On average, revenue is $59.42 thousand less in Quarter 2 as compared to
Quarter 4 each year.
Quarter 2 revenue decreases by $59.42 thousand as revenue values in Quarters
1, 2, and 4 increase.
Revenue decreases by $59.42 thousand on average every Quarter 2.
As time increases by one quarter, revenue decreases by $59.42 thousand on
average.
Transcribed Image Text:In the following time series linear regression equation, this time in quarters and y is revenue in thousands of dollars. ýt = 443.2 - 59.51Qtr1 – 59.42Qtr2 + 78.87Qtr3 Interpret the regression coefficient for the Qtr2 variable. On average, revenue is $59.42 thousand less in Quarter 2 as compared to Quarter 4 each year. Quarter 2 revenue decreases by $59.42 thousand as revenue values in Quarters 1, 2, and 4 increase. Revenue decreases by $59.42 thousand on average every Quarter 2. As time increases by one quarter, revenue decreases by $59.42 thousand on average.
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