The paired sample data of the age and selling price of houses result in a linear

Question

The paired sample data of the age and selling price of houses result in a linear correlation coefficient very close to 0. Older houses tend to cost more. Describe the error in the stated conclusion. A. With a linear correlation coefficient very close to 0, we should conclude that there is not a linear correlation, so there does not appear to be a correlation between age and selling price as the conclusion incorrectly suggests. B. A linear correlation coefficient very close to 0 implies that there is a linear correlation between the averages, but a correlation between the averages does not imply a correlation between individuals as the conclusion incorrectly suggests. C. A linear correlation coefficient very close to 0 implies that there is a linear correlation, but it could be a negative correlation instead of a positive correlation as the conclusion incorrectly suggests. D. Correlation does not imply causality, as the conclusion incorrectly suggests.

Explanation / Answer

Here we have given that the correlation between age of houses and selling price of houses and it is near to 0.

so this implies that there is no relationship between age of houses and selling price.

So correct answer is,

A) With linear correlation coefficient very close to 0 . We should conclude that there is not a linear correlation, So there does not appear to be correlation between age and selling price as conclusion incorrectly suggests.

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