Question textIn 2014, Tom took most of his savings ($6,000) and invested it in a managed fund which is based on cash, shares and real estate investments. Tom received the following summary of the yearly value of his investment in a recent statement - consider this to be the original set of data. The year data can be converted to represent the number of years since the initial investment - consider this to be the adjusted set of data. years = np.arange(2014, 2025) balance = np.array([6000, 6495.65, 7690.43, 8155.08, 8900.29, 9996.97, 11941.28, 12598.42, 14264.11, 17930.75, 20596.31])num_years = years - years[0] a) Fit a linear model ([math: y=a0+a1x]) using the original set of data. [math: a0]: Answer 1 Question 1[input] (0 decimal places)[math: a1]: Answer 2 Question 1[input] (0 decimal places) b) Then, fit a linear model ([math: y=a0+a1x]) using the adjusted set of data.[math: a0]: Answer 3 Question 1[input] (0 decimal places)[math: a1]: Answer 4 Question 1[input] (0 decimal places) c) Fit a power law model ([math: y=αxβ]) to the original set of data. [math: α]: Answer 5 Question 1[input] (2 decimal places)[math: β]: Answer 6 Question 1[input] (0 decimal places) d) Fit a power law model ([math: y=αxβ]) to the adjusted set of data. [math: α]: Answer 7 Question 1[input] (0 decimal places)[math: β]: Answer 8 Question 1[input] (4 decimal places) e) Fit an exponential model ([math: y=αeβx]) to the original set of data. [math: α]: Answer 9 Question 1[input] (2 decimal places)[math: β]: Answer 10 Question 1[input] (4 decimal places)f) Fit an exponential model ([math: y=αeβx]) to the adjusted set of data. [math: α]: Answer 11 Question 1[input] (0 decimal places)[math: β]: Answer 12 Question 1[input] (4 decimal places)Check Question 1多项填空题