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Ksju [112]
3 years ago
10

If you have a curvilinear relationship, then: (Hint: The two most important sources of bias in this context are probably lineari

ty and normality.)
a. It is not appropriate to use Pearson's correlation because it assumes a linear relationship between variables.
b. Pearson's correlation can be used in the same way as it is for linear relationships.
c. You can use Pearson's correlation; you just need to remember that a curve indicates that the variables are not linearly related.
d. Transforming the data won't help.
Mathematics
1 answer:
I am Lyosha [343]3 years ago
3 0

Answer:

b. Pearson's correlation can be used in the same way as it is for linear relationships

Explanation:

Pearson's correlation can also be termed "simple linear regression analysis" is a statistical measure used to determine if two numeric variables are significantly linearly related. Pearson's correlation coefficient is used to measures the statistical relationship or association between two continuous variables.

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Consider the provided information.

If the selling price of two item is same and one item sold at a profit of x % and other at a loss of x % in that case total sale result loss:

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It is given that he had a profit of 20 percent on the sale of one of the shares but a loss of 20 percent on the sale of the other share, where the selling price is $96 each.

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