Smith & Wright, a research firm for the real estate industry, studied the relation between I = annual income (in thousands of dollars) and y = sale price of house purchased (in thousands of dollars). A random sample of data was collected from mortgage applications for home sales in the region of the study, and is given in the table. Annual Income House Price 57 111.6 98 176.6 67 137.3 85 136.5 51 133.5 109 192.3 72 124.2 69 182.5 81 155.8 Conduct a linear regression. Use the results to answer the following questions. a. What is the value of the correlation coefficient (round to 3 decimal places)? What does the value tell you about the linear relationship between the annual income and the price of house purchased? Correlation coefficient: This indicates: O perfect negative linear correlation O fairly strong negative linear correlation O perfect positive linear correlation O very weak negative linear correlation O fairly strong positive linear correlation O very weak positive linear correlation O no linear correlation b. What is the equation of the Least Squares line? Round the parameter values (slope and y intercept) to 2 decimal places. y = c. If a buyer's annual income increases by $1000, the model's predicted change in DOLLARS of the sale price of the house they will purchase is: an Select an answer v of s Select an answer (NO Increase decrease NITS!) Question Help: Message instructor