The right option is c, The linear least-squares regression line is not appropriate for the data. A straight line is not an effective way to summarize the data.
A least-squares regression line, which minimizes the vertical distance between the data points and the regression line, is the line that best fits a linear connection between two variables when the data indicates such a relationship.
Given that the terms "linear least squares" and "linear regression" relate to two distinct concepts, we should differentiate between them. The former refers to fitting a model that is a linear function of the independent variable, and the latter refers to fitting a model that is linear in the parameters.
To understand more about least-squares regression, have a look at this example:
brainly.com/question/24848242
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The right question is:
Suppose we fit the least-squares regression line to a set of data. If a plot of the residuals shows a curved pattern,
A. a straight line is not a good summary of the data.
B. the correlation must be 0.
C. the correlation must be positive.
D. outliers must be present.
E. r2 = 0.
