Annual high temperatures in a certain location have been tracked for several years. Let r represent the number of years after 2000 and y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to three decimal places). y 4 38.32 37 6. 38.08 7 42.36 81 42.04 9. 43.32 10 43 11 45.08 12 45.06 13 45.24 14 45.22 15 48.4 16 46.28 The equation is ŷ Interpret the slope: O For each additional year, the annual high temperature will increase by 34.802 degrees on average. O For each additional 0.823 years, the annual high temperature will increase by 1 degree on average. O For each additional 34.802 years, the annual high temperature will increase by 1 degree on average. O For each additional year, the annual high temperature will increase by 0.823 degrees on average. Interpret the y-intercept of the equation: O In 2004, the temperature was about 0.823. O In 2004, the temperature was about 34.802. O In 2016, the temperature was about 46.28. O In 2000, the temperature was about 34.802.

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Annual high temperatures in a certain location have been tracked for several years. Let I represent the
number of years after 2000 and y the high temperature. Based on the data shown below, calculate the
linear regression equation using technology (each constant to three decimal places).
4
38.32
37
38.08
42.36
8
42.04
6.
43.32
10
43
11
45.08
12.
45.06
13
45.24
14
45.22
15
48.4
16
46.28
The equation is ŷ
Interpret the slope:
O For each additional year, the annual high temperature will increase by 34.802 degrees on average.
O For each additional 0.823 years, the annual high temperature will increase by 1 degree on average.
O For each additional 34.802 years, the annual high temperature will increase by 1 degree on average.
O For each additional year, the annual high temperature will increase by 0.823 degrees on average.
Interpret the y-intercept of the equation:
O In 2004, the temperature was about 0.823.
O In 2004, the temperature was about 34.802.
O In 2016, the temperature was about 46.28.
OIn 2000, the temperature was about 34.802.
Transcribed Image Text:Annual high temperatures in a certain location have been tracked for several years. Let I represent the number of years after 2000 and y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to three decimal places). 4 38.32 37 38.08 42.36 8 42.04 6. 43.32 10 43 11 45.08 12. 45.06 13 45.24 14 45.22 15 48.4 16 46.28 The equation is ŷ Interpret the slope: O For each additional year, the annual high temperature will increase by 34.802 degrees on average. O For each additional 0.823 years, the annual high temperature will increase by 1 degree on average. O For each additional 34.802 years, the annual high temperature will increase by 1 degree on average. O For each additional year, the annual high temperature will increase by 0.823 degrees on average. Interpret the y-intercept of the equation: O In 2004, the temperature was about 0.823. O In 2004, the temperature was about 34.802. O In 2016, the temperature was about 46.28. OIn 2000, the temperature was about 34.802.
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