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For which data set is a linear regression most reasonable

User Carmine
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If your data consists of scores from variables that are correlated or those that you already correlated with, then the most reasonable data statistical analysis would be a linear regression. This is used usually in order to determine if one variable predicts the other.
User Matthew Trent
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Answer:

C. a set of four data pairs with a correlation coefficient r = –0.8

Explanation:

The options for this answer are

A. a set of nine data pairs with a correlation coefficient r = –0.4

B. a set of five data pairs with a correlation coefficient r = 0.3

C. a set of four data pairs with a correlation coefficient r = –0.8

D. a set of six data pairs with a correlation coefficient r = 0.6

The correlation coefficient is a statistical measure about the relationship between two variables. Specifically, it tells if there's a positive or negative correlation, and how strong or weak it is.

The interval of a correlation coefficient is from -1 to 1, and the nearer the value gets to zero, the less correlation exist between variables. If the coefficient is near 1, that means there is a strong positive correlation, and if the coefficient is near -1, that means there's a strong negative correlation.

So, in this case, option C shows a correlation coefficient of -0.8, which is the "highest" coefficient among options, this means that it represents the strongest correlation among options.

Therefore, the best data set that fits a linear correlation is C.

User Silverfighter
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