Questions: Posttest: Data and Mathematical Modeling Three runners competed in a race. Data were collected at each mile mark for each runner. If the runner ran at a constant pace, the data is linear. A regression line was fitted to their data. Use the residual plots to decide which data set is best fit by the regression line, and the runner that kept the most consistent pace. Runner A Runner B Runner C

Posttest: Data and Mathematical Modeling

Three runners competed in a race. Data were collected at each mile mark for each runner. If the runner ran at a constant pace, the data is linear. A regression line was fitted to their data. Use the residual plots to decide which data set is best fit by the regression line, and the runner that kept the most consistent pace.

Runner A
Runner B
Runner C
Transcript text: Posttest: Data and Mathematical Modeling Three runners competed in a race. Data were collected at each mile mark for each runner. If the runner ran at a constant pace, the data is linear. A regression line was fitted to their data. Use the residual plots to decide which data set is best fit by the regression line, and the runner that kept the most consistent pace. Runner A Runner B Runner C
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Solution

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Solution Steps

Step 1: Analyze the Residual Plots

The residual plot for Runner C shows the smallest residuals, with the points clustered tightly around the horizontal axis. This indicates that the data points for Runner C are closest to the regression line.

Step 2: Interpret the Residual Plots in Context

Smaller residuals mean the runner's pace was more consistent. A consistent pace would mean their times at each mile marker are close to the predicted times from a linear model. Larger residuals indicate more variation in pace.

Step 3: Determine the Most Consistent Runner

Since Runner C's residual plot shows the smallest residuals and the tightest clustering around the horizontal axis, Runner C maintained the most consistent pace.

Final Answer

Runner C kept the most consistent pace.

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