APPLICATION OF SUPERVISED LEARNING
LINEAR REGRESSION
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Suppose we fit a least-squares regression line to a set of bivariate data. If a residual plot shows a curved pattern, what must be true about the data?
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A LSRL is not a good model for the data.
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The correlation must be 0
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The coefficient of determination must be small.
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Outliers must be present.
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The standard deviation of the residuals must be large
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Explanation:
Detailed explanation-1: -Since the residuals show how far the data falls from the LSRL, examining the values of the residuals will help us to gauge how well the LSRL describes the data. The sum of the residuals is always 0 so the plot will always be centered around the x-axis.
Detailed explanation-2: -The least-squares regression line is fit to a set of data. If one of the data points has a positive residual, then the correlation between the values of the response and explanatory variables must be positive.
There is 1 question to complete.