Select [b]all[/b] the values for [math]r[/math] that indicate a positive slope for the line of best fit.
The correlation coefficient, [math]r[/math], is given for several different linear models for a data set. Which value for r indicates the best fit for the data?
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[/img]
The data in the table displays the results of the study. [br][br][img]data:image/png;base64,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[/img][br][br]Create the line of best fit for the data in the table.
What is the equation of the line of best fit for this data? Round numbers to two decimal places.
What is the slope of the line of best fit? What does it mean in this situation? Is this realistic?
What is the [math]y[/math]-intercept of the line of best fit? What does it mean in this situation? Is this realistic?[br]
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[/img][/td][td][img]data:image/png;base64,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[/img][/td][/tr][/table][br]Which point does the line estimate the best?
Which point does the line estimate the worst?
Tyler creates a line of best fit and finds that the residual for the point [math]\left(1.4,1250\right)[/math]is -132. The point [math]\left(1.2,1364\right)[/math]has a residual of 117. Interpret the meaning of 117 in the context of the problem.