11. For temperature (x) and number of ice cream cones sold per hour (y). (65, 8), (70, 10), (75, 11), (80,13), (85, 12), (90, 16). Interpret the coefficient of determination. Optional Answers: 1. 88.2% of the variability in the number of cones sold is explained by the least-squares regression model. 2. 93.9% of the variability in the number of cones sold is explained by the least-squares regression model. 3. 88.2% of the variability in the temperature is explained by the least-squares regression model. 4. 93.9% of the variability in the temperature is explained by the least-squares regression model.

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11. For temperature (x) and number of ice cream cones sold per hour (y).
(65, 8), (70, 10), (75, 11), (80,13), (85, 12), (90, 16). Interpret the coefficient of determination.
Optional Answers:
1. 88.2% of the variability in the number of cones sold is explained by the least-squares
regression model.
2. 93.9% of the variability in the number of cones sold is explained by the least-squares
regression model.
3. 88.2% of the variability in the temperature is explained by the least-squares regression
model.
4. 93.9% of the variability in the temperature is explained by the least-squares regression
model.
Transcribed Image Text:11. For temperature (x) and number of ice cream cones sold per hour (y). (65, 8), (70, 10), (75, 11), (80,13), (85, 12), (90, 16). Interpret the coefficient of determination. Optional Answers: 1. 88.2% of the variability in the number of cones sold is explained by the least-squares regression model. 2. 93.9% of the variability in the number of cones sold is explained by the least-squares regression model. 3. 88.2% of the variability in the temperature is explained by the least-squares regression model. 4. 93.9% of the variability in the temperature is explained by the least-squares regression model.
Expert Solution
Step 1

From given data,

X Y X*Y X*X Y*Y
65 8 520 4225 64
70 10 700 4900 100
75 11 825 5625 121
80 13 1040 6400 169
85 12 1020 7225 144
90 16 1440 8100 256

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