The linear correlation between an independent (x) and dependent (y) variable   A. Is the foundation for simple (bivariate) regression   B. Does not indicate a causal relationship, though one might exist   C. Can be direct, inverse, or nonexistent   D. Can be used to predict the value of y for any observed value of x   E. All of the above   F. None of the above

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
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Chapter5: A Survey Of Other Common Functions
Section5.6: Higher-degree Polynomials And Rational Functions
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The linear correlation between an independent (x) and dependent (y) variable

  A.

Is the foundation for simple (bivariate) regression

  B.

Does not indicate a causal relationship, though one might exist

  C.

Can be direct, inverse, or nonexistent

  D.

Can be used to predict the value of y for any observed value of x

  E.

All of the above

  F.

None of the above

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