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myopenmath.com [Google] , you will find data regarding this study. The variables are: . Age: The age of a house, in years . Size: The size of a house, in square feet . Rooms: The number of rooms in a house AvgBill: The average monthly heating bill, in dollars. Using the variables for Age, Size, and Rooms, find a linear regression model that may predict the average monthly heating bill: A) What is the regression equation? AvgBill = Age Size Rooms (Round to two decimal places for each coefficient) B) What is the p-value for the overall model? P= (Give four places. Enter 0 if the p value is less than 0.0001) C) What is the adjusted R-squared value? R2 (adjusted = ( Give four places ) Note: As the text states (p349), using just R is "acceptable when there is just a single variable. However, it becomes less helpful when there are many variables. The regular R2 is a biased estimate of the amount of variability explained by the model when applied to a new sample of data. To get a better estimate, we use the adjusted R2 ." D) Notice that NOT all of the p-values for the slope coefficients are below 0.05. What is the value of the highest p-value associated with a slope coefficient? Highest p value = (Give four places) A N R T U O Q W tab A S D G H K T caps lock M Z X C V B N