In calculating the Pearson correlation coefficient, we assume that: a. the relationship we are trying to measure is curvilinear. b. the variables have been measured using interval - or ratio-scaled measures. c. the variables we want to analyze have a binomially distributed population. d. when the correlation coefficient is weak, there is a consistent, systematic relationship between the two variables. e. when the correlation coefficient is strong and significant, the two variables are associated in a curvilinear fashion.

Question

Mathematics

Lucille Powell

15 December, 20:43

In calculating the Pearson correlation coefficient, we assume that: a. the relationship we are trying to measure is curvilinear. b. the variables have been measured using interval - or ratio-scaled measures. c. the variables we want to analyze have a binomially distributed population. d. when the correlation coefficient is weak, there is a consistent, systematic relationship between the two variables. e. when the correlation coefficient is strong and significant, the two variables are associated in a curvilinear fashion.

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Patrick Fletcher · Answer 1

Answer: the correct answer is b the variables have been measured using interval - or ratio-scaled measures.

Step-by-step explanation:

The Pearson correlation measures the level of association between two variables and these variables are shown in a table and are measured in intervals like this:

X Y

10 25

20 35

30 45

The Pearson product-moment correlation coefficient (Pearson's correlation, for short) is a measure of the strength and direction of association that exists between two variables measured on at least an interval scale.

Correlation coefficient measures the level of the association between two variables (x and y). Pearson correlation analysis method is the most used one. The formula for the correlation coefficient is : r=∑ (x-mx) (y-my) √∑ (x-mx) 2∑ (y-my) 2. mx and my are the means of x and y variables.