Which of the following statements about the correlation coefficient is FALSE? It measures the strength and direction of a linear relationship. A value of 0 indicates no linear relationship. It can only take positive values. A value of -1 indicates a perfect negative linear relationship.

When is the correlation coefficient equal to 0?(1 Point)a) When there is a strong positive linear relationship.b) When there is a strong negative linear relationship.c) When there is no linear relationship.d) When there is a curvilinear relationship.

Which statement about correlation is FALSE?The correlation of a data set can be positive, negative, or 0.Correlation is used to define the variables of only non-linearly related data sets.Correlation between the variables of the data set can be measured.Correlation is the degree to which the two variables of a data set resemble each other.

What does a correlation coefficient of -1 indicate? No linear relationship between two variables. A perfect positive linear relationship between two variables. A perfect negative linear relationship between two variables. The variables are unrelated.

Correlation can either be positive or negative but it is a linear relationship. The larger the absolute value the stronger the relationship and we evaluate it through comparison of the extreme values of 0 and 1Question 3Answera.Falseb.True

We first introduce the concept of correlation in the Section 2.5 notes.Consider a linear model of the relationship between two quantitative variables in which the slope coefficient is non-zero. Which of the following statements about the slope coefficient and the correlation r between the two variables is correct?Question 1Select one:a.The slope coefficient could be negative when the correlation coefficient is positiveb.The slope coefficient and the correlation coefficient should have the same sign (both positive, or both negative)c.The slope coefficient could be positive when the correlation coefficient is negatived.The correlation coefficient can only be a positive value (regardless of whether the slope is positive or negative)Clear my choice