Which of the following statements about the correlation,
r, between Y and X is NOT true?
A. r measures the strength of the linear association
between Y and X.
B. r does not provide any information about the strength of non-linear relationships.
C. r = 0 means there is no relationship between Y and X.
D. Calculating r is not appropriate if the distributions of Y and X are skewed with outliers.
Option : C r=0 means there is no relationship between Y and X.
Here r=0 But X and Y are related.
Y=X2
Which of the following statements about the correlation, r, between Y and X is NOT true?...
Which of the following are true statements about the correlation coefficient r? I. A correlation coefficient of .3 means that 30% of the points are highly correlated. II. The square of the correlation measures the proportion of the y-variance that is predictable from a knowledge of x. III. Perfect correlation, that is, when the points lie exactly on a straight line is r = 0.
Which of the following best describes correlation? a.) Correlation measures the strength of the relationship between any two variables. b.) Correlation measures the strength of the linear association between two categorical variables. c.) Correlation measures how much a change in the explanatory variable causes a change in the response variable. d.) Correlation measures the strength of the linear relationship between two quantitative variables.
Which of the following statements regarding the correlation coefficient is not true? A) The correlation coefficient has values that range from-1.0 to 1.0 inclusive. B) The correlation coefficient measures the strength of the linear relationship between two numerical variables C) A value of 0.00 indicates that two variables are perfectly linearly correlated D) All of these are true statements
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The value of r obtained by calculating the correlation between X and Y is the same as the correlation between Y and X. A. True B. False
14. Multiple Choice Variables x and y have a correlation coefficient of r = 0.89. Which statement is best? a. There is a strong positive association between x and y and a straight line fit to the data cannot be substantially improved by fitting a curve to the data. b. There is a strong positive association between x and y and a straight line fit to the data can certainly be substantially improved by fitting a curve to the data....
Determine whether each of the following statements regarding the correlation coefficient is true or false. The correlation coefficient equals the proportion of times that two variables lie on a straight line. The correlation coefficient will be +1.0 if all the data points lie on a perfectly horizontal straight line. The correlation coefficient measures the strength of any relationship that may be present between two variables. The correlation coefficient must always lie between –1.0 and +1.0.
1. When no linear relationship exists between variable X and variable Y, r equals which of the following? a) −∞-∞ b) -1 c) 0 d) +1 e) +∞+∞ 2. Pearson’s r correlation measures the relationship between which of the following? a) Two continuous variables b) Two categorical variables c) One continuous and one categorical variable
Which of the following statements regarding regression and correlation are true? (There may be more than one correct answer.) a. A value of the linear correlation, r, near -1 means the data is tightly bundled around a line, and predictions within the scope of data are very reliable. b. When the slope of a linear regression equation is near 0, then the linear correlation between the two variables must also be near 0. c. The average error between the actual...
True or False: if the r(correlation coefficient) is closer to 1, the slope(beta) will be larger to reflect a stronger linear relationship between X and Y .