Search

1 of 8 0-day streak

Recommend a transformed regression model

Question 1 of 8

Calculator allowed

The explanatory variable is input setting (units), symbol i; the response variable is signal power (mW), symbol P. Fit each candidate to the displayed raw observations, using exact square and reciprocal values. Round each base-10 logarithmic coordinate to three decimal places before fitting; retain full coefficients of that fit. Report explained variation to the nearest whole percentage point on that candidate's fitted response scale

The displayed data contain 6 cases and are used to assess several one-axis transformed regression models

signal power (mW)input setting (units)
\(\frac{1}{50}\)2
\(\frac{1}{5}\)3
204
2,0005
20,0006
200,0007

Each residual plot has a horizontal zero reference line. Use the original explanatory-variable and response-variable roles shown by the axis labels

Model B residual scatterplot with 6 plotted coordinates. The horizontal axis is input setting (units) and the vertical axis is Residual in log₁₀(signal power); the horizontal reference line is zero. Coordinates shown to at most six decimal places are (2.000000, 0.047619), (3.000000, -0.438095), (4.000000, 0.076190), (5.000000, 0.590476), (6.000000, 0.104762), (7.000000, -0.380952).246-0.500.5input setting (units)Residual inlog₁₀(signal power)
Model A residual scatterplot with 6 plotted coordinates. The horizontal axis is square of input setting and the vertical axis is Residual in signal power (mW); the horizontal reference line is zero. Coordinates shown to at most six decimal places are (4.000000, 34492.599908), (9.000000, 15841.662541), (16.000000, -10250.101773), (25.000000, -41842.113035), (36.000000, -64874.571243), (49.000000, 66632.523602).2040-50,000050,000square of input settingResidual in signalpower (mW)

Use this exercise rule: first reject clear residual structure, then prefer the larger reported percentage among the remaining candidates. If reported percentages tie, use the following reporting preference, from first to last: input square; input reciprocal or response square; input logarithm or response reciprocal; response logarithm. This is a stated task preference, not a universal ranking of transformations. Percentages for different response scales do not describe the same original-response variation

(a)1 mark

Which complete set of one-axis transformations is represented by the candidate residual plots?

(b)1 mark

Which candidate should not be used?

(c)1 mark

Which model should be recommended? Apply the residual-plot rule before comparing r²