What is an advantage of the correlation coefficient over the covariance?
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What is an advantage of the correlation coefficient over the covariance?
Correlation is better than covariance for these reasons: 1 — Because correlation removes the effect of the variance of the variables, it provides a standardized, absolute measure of the strength of the relationship, bounded by -1.0 and 1.0.
What are the strengths of using correlations?
Correlation allows the researcher to clearly and easily see if there is a relationship between variables. This can then be displayed in a graphical form.
What is the advantage of the correlation coefficient over the covariance quizlet?
Comparing a numerical variable across two or more subpopulations is known as a comparison problem. The advantage that correlation has over covariance is that the former has a set lower and upper limit. Correlation is a single-number summary of a scatterplot.
What are the strengths and weaknesses of correlations?
Strengths and weaknesses of correlation
| Strengths: | Weaknesses |
|---|---|
| Useful as a pointer for further, more detailed research. | Lack of correlation may not mean there is no relationship, it could be non-linear. |
Which correlation coefficient represents the strongest correlation?
Explanation: According to the rule of correlation coefficients, the strongest correlation is considered when the value is closest to +1 (positive correlation) or -1 (negative correlation). A positive correlation coefficient indicates that the value of one variable depends on the other variable directly.
What level of correlation is good?
Correlation Coefficient = +1: A perfect positive relationship. Correlation Coefficient = 0.8: A fairly strong positive relationship. Correlation Coefficient = 0.6: A moderate positive relationship. Correlation Coefficient = 0: No relationship.
What is one of the strengths of a correlational study?
The variables that get studied with correlational research help us to find the direction and strength of each relationship. This advantage makes it possible to narrow the findings in future studies as needed to determine causation experimentally as needed.
What are the limitations of the correlation coefficient?
An important limitation of the correlation coefficient is that it assumes a linear association. This also means that any linear transformation and any scale transformation of either variable X or Y, or both, will not affect the correlation coefficient.