We will proceed with trying to predict a house's cost based on its size by performing linear regression. cost (dollars) square feet $215,000.00 1635 $270,000.00 2578 $650,000.00 4207 $170,000.00 1500 $260,000.00 3200 $194,000.00 1669 $183,000.00 1833 $217,000.00 1675 $550,000.00 3347 $319,000.00 2767 $135,000.00 1223 $199,000.00 1406 $120,000.00 1317 $210,000.00 1657 $159,000.00 1105 $172,000.00 1773 $290,000.00 2281 $139,000.00 1582 $120,000.00 1001 $143,000.00 1149 Which variable is the explanatory variable (x)? Answer in complete sentence(s). Which variable is the response variable (y)? Answer in complete sentence(s). Calculate the slope of the regression line: b=rsy/sx. Round answer to 2 decimal places. Remember to write equation and show work using equation editor (started below). Introduce calculations with complete sentence(s). b=rsy/sx= Write a sentence to interpret the slope. (Use the format provided in lecture videos to receive any credit.) Calculate the y-intercept of the regression line: a=y-bx. Round answer to 2 decimal places. Remember to write equation and show work using equation editor. Introduce calculations with complete sentence(s). a=y-bx= Does it make sense to interpret the y-intercept? Explain. Answer in complete sentence(s). Write a sentence to interpret the y-intercept (even if you think it's inappropriate, do it anyway). Use the format provided in videos to receive any credit. What is the linear regression equation: y^=a+bx? Introduce calculations with complete sentence(s). y^=a+bx=