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A regression was done for 20 cities with latitude as the explanatory variable (x) and average January temperature as the response variable (y). The latitude is measured in degrees and average January temperature in degrees Fahrenheit. The latitudes ranged from 26 (Miami) to 47 (Duluth) The regression equation is $\hat{y}$ = 49.4 - 0.313x.
-The total sum of squares (SSTO) = 4436.6, and the error sum of squares (SSE) = 1185.8. What is the value of r² the proportion of variation in y explained by its linear relationship with x?

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Use the following information for questions:
A regression was done for 20 cities with latitude as the explanatory variable (x) and average January temperature as the response variable (y). The latitude is measured in degrees and average January temperature in degrees Fahrenheit. The latitudes ranged from 26 (Miami) to 47 (Duluth) The regression equation is

\hat{y}

= 49.4 - 0.313x.
-The total sum of squares (SSTO) = 4436.6, and the error sum of squares (SSE) = 1185.8. What is the value of r² the proportion of variation in y explained by its linear relationship with x?

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The Answer of Use the following information for questions: A regression was done for 20 cities with latitude as the explanatory variable (x) and average January temperature as the response variable (y). The latitude is measured in degrees and average January temperature in degrees Fahrenheit. The latitudes ranged from 26 (Miami) to 47 (Duluth) The regression equation is $\hat{y}$ = 49.4 - 0.313x. -The total sum of squares (SSTO) = 4436.6, and the error sum of squares (SSE) = 1185.8. What is the value of r² the proportion of variation in y explained by its linear relationship with x?

Use the Following Information for Questions: a Regression Was y^\hat{y}y^​

Use the Following Information for Questions:
a Regression Was $\hat{y}$