Question

If you find a Pearson's correlation of zero between two continuous variables, this means: A. There...

If you find a Pearson's correlation of zero between two continuous variables, this means:

A. There is no relationship between the two variables

B. There is a strong relationship between the two variables

C. There may be a non-linear relationship between the two variables

D. Two of these answers are correct

Homework Answers

Answer #1

Answer: Pearson's coefficient of correly measure the degree of linear relationship between two variable. The range of correlation coefficient is -1 to 1.

r=-1 means there is negative correlation between variables.

r=0 means there is no relationship or non linear relationship between the variable.

r=1 means there is perfect positive correlation between two variables.

So the option A and C are correct.

A. There is no relationship between the two variable

C. There may be a non-linear relationship between the two variables

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Introduced in Chapter 10, Pearson's r measures the linear _____ between two _____ level variables. a....
Introduced in Chapter 10, Pearson's r measures the linear _____ between two _____ level variables. a. correction, interval b. correlation, nominal c. correction, nominal d. correlation, interval
A) Two variables have a high covariance. This means the two variables have a strong relationship....
A) Two variables have a high covariance. This means the two variables have a strong relationship. T/F B) For a variable x, the sample mean is 8 and the sample standard deviation is 2. One of the observations is 15. Is this observation an outlier? Group of answer choices Yes, the z-score is greater than 3 No, the z-score is between -3 and 3 Yes, the z-score is between -3 and 3 No, the z-score is less than -3 C)...
Which statement explains why correlation could be 0 even if a strong relationship between two variables...
Which statement explains why correlation could be 0 even if a strong relationship between two variables existed? Group of answer choices Since the correlation is 0, there is no strong relationship between the two variables; and a scatterplot would be misleading. Correlation can be 0 even if there is a strong linear relationship between the variables. Correlation only measures the strength of the relationship between two variables when the units of the two variables are the same. Correlation does not...
A value of -1 for the coefficient of correlation between two variables means that the two...
A value of -1 for the coefficient of correlation between two variables means that the two variables are ________________. a)somewhat strongly related b)weakly related c)perfectly related d)very weakly related e)not related at all 2) If the correlation coefficient between variables X and Y is roughly zero, then ______. a)Y is independent of X b)Y is dependent on X c)there is a linear correlation between Y and X d)Y is not necessarily independent of X e)Y is caused by X. 3)...
A Correlation Coefficient is a measurement of the relationship between two variables. A positive correlation means...
A Correlation Coefficient is a measurement of the relationship between two variables. A positive correlation means that as one variable increases, the second variable increases too. A negative correlation means that as one variable increases, the second variable decreases, or as one variable decreases, the second variable increases. Positive and negative correlations exists in nature, science, business, as well as a variety of other fields. Please watch the following video for a graphical explanation of the correlation coefficient: For Discussion...
A negative correlation between variables X and Y means that ____. A. the correlation between variables...
A negative correlation between variables X and Y means that ____. A. the correlation between variables X and Y is very weak B. scores on variable X has little predicting power on the corresponding scores on variable Y C. higher scores on variable X correspond to lower scores on variable Y and vice versa D. Higher scores on variable X correspond to higher scores on variable Y while lower scores on variable X correspond to lower scores on variable Y...
When you are presented with a Pearson’s correlation coefficient between two variables for which an increase...
When you are presented with a Pearson’s correlation coefficient between two variables for which an increase in one predicts a decrease in the other, and vice versa, the Pearson’s number will be zero; the Pearson number is only meaningful if the variables move in the same direction as one another close to -1 if the correlation is strong, negative but near zero if the correlation is weak close to -1 if the correlation is strong, close to +1 if the...
A coefficient of correlation of -0.9 indicates the relationship between the two variables is (a) weak...
A coefficient of correlation of -0.9 indicates the relationship between the two variables is (a) weak and negative (b) strong and positive (c) strong and negative
Correlation is a visual method for determining the relationship between two variables... including linear, curve linear,...
Correlation is a visual method for determining the relationship between two variables... including linear, curve linear, strong, weak, positive, negative, and no relationships. The correlation coefficient is a mathematical reflection of that relationship. Regression analysis is the same thing as the correlation coefficient. True or False
Suppose the correlation coefficient between two variables is found to be 0.83. Which of the following...
Suppose the correlation coefficient between two variables is found to be 0.83. Which of the following statements are true? small values of one variable are associated with large values of the other variable the relationship between the variables is weak a scatter plot of the points would show an upward trend low values of one variable tend to be paired with low values of the other variable there is a strong positive curvilinear relationship between the variables there is a...