A temperature dataset gives y = mean April temperature (Fahrenheit) and x = geographic latitude for 20 0.S. cities. The simple linear regression equation for the sample is ŷ = 119 - 1.64x. (a) The value of latitude for a certain city is 41. What is the predicted April temperature for this city? (Round your answer to the nearest tenth.) degrees Fahrenheit (b) The mean April temperature for this city is 48. What is the residual for the city? (Round your answer to the nearest tenth.) degrees Fahrenheit You may need to use the appropriate table in the Appendix of Tables to answer this question.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Chapter4: Equations Of Linear Functions
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A temperature dataset gives y mean April temperature (Fahrenheit) and x = geographic latitude for 20 U.S. cities. The simple
linear regression equation for the sample is ŷ = 119 - 1.64x.
(a) The value of latitude for a certain city is 41. What is the predicted April temperature for this city? (Round your answer
to the nearest tenth.)
degrees Fahrenheit
(b) The mean April temperature for this city is 48. What is the residual for the city? (Round your answer to the nearest
tenth.)
degrees Fahrenheit
You may need to use the appropriate table in the Appendix of Tables to answer this question.
Transcribed Image Text:A temperature dataset gives y mean April temperature (Fahrenheit) and x = geographic latitude for 20 U.S. cities. The simple linear regression equation for the sample is ŷ = 119 - 1.64x. (a) The value of latitude for a certain city is 41. What is the predicted April temperature for this city? (Round your answer to the nearest tenth.) degrees Fahrenheit (b) The mean April temperature for this city is 48. What is the residual for the city? (Round your answer to the nearest tenth.) degrees Fahrenheit You may need to use the appropriate table in the Appendix of Tables to answer this question.
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