What is the primary difference between covariance and correlation?Question 3Answera.Covariance is always positive, correlation can be negativeb.Covariance is dimensionless, correlation has unitsc.Covariance measures strength and direction, correlation only directiond.Correlation standardizes covariance
Question
What is the primary difference between covariance and correlation?Question 3Answera.Covariance is always positive, correlation can be negativeb.Covariance is dimensionless, correlation has unitsc.Covariance measures strength and direction, correlation only directiond.Correlation standardizes covariance
Solution
The primary difference between covariance and correlation lies in their measurements and interpretations.
Covariance measures the degree to which two variables move together or vary together. It has units that are derived from the units of the two variables. However, the problem with covariance is that it is not standardized. Therefore, covariance can range from negative infinity to positive infinity. Thus, the value of covariance doesn’t really tell you about the strength of the relationship between the variables.
On the other hand, correlation is a standardized measure of covariance. It is dimensionless. In other words, it is a unit-free measure of the relationship between variables. Correlation is derived from the covariance of two variables divided by the product of their standard deviations. Correlation coefficients range from -1 to 1. The closer the correlation coefficient is to -1 or 1, the stronger the relationship between the variables.
So, the correct answer is d. Correlation standardizes covariance.
Similar Questions
Assertion (A) Broadly, there only two types of correlation i.e., positive and negative.Reason (R) The correlation is said to be positive when the variables move together in the same direction, the correlation is negative when they move in opposite directions.
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 positive covariance between two variables indicate?Question 1Answera.Variables move in opposite directionsb.There is no relationship between variablesc.One variable is constantd.Variables move together in the same direction
Which of the following are measured by correlation coefficienta.Linear association between two random variablesb.Direction of relationship between two variables (positive or negative association)c.A unit free value for the strength of linear relationship between two random variablesd.All of the above
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
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