Question textA company is analysing how internet traffic (in gigabytes per day) scales with the number of users on its network. To investigate the nature of this relationship, they tested linear, exponential, and power law models using the scatter plots and residual plots shown below. Natural logarithms were used for the transformations.a. Which of the following is correct regarding the association between the number of users and internet traffic? [1 mark] Multiple choice 1 Question 9There is no association between the number of users and internet traffic. There is a positive association between the number of users and internet traffic. There is a negative association between the number of users and internet traffic. b. Which of the following is the most appropriate model for the relationship between the number of users and internet traffic? [1 mark] Multiple choice 2 Question 9linear modelexponential modelpower law model c. Which equation best describes the relationship between the number of users and internet traffic? [1 mark] Multiple choice 3 Question 9 Please answer all parts of the question.多项填空题
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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
Which of the statement below is true about the coefficient of determination, r2?
这句话是真还是假？ “回归线总可以用来做出可靠的预测。”
The R^2 value:
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