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How would you describe a Correlation Coefficient in your own words?
Wiki User
∙ 11y ago
The strength of the relationship between 2 variables.
Ex. -.78
Wiki User
∙ 11y ago
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When two variables are found to be unrelated the correlation coefficient would be?
Zero.
What type of correlation is one that curved?
Correlation cannot accurately describe any type of curve. The correlation of a curve would be a linear approximation rather than an accurate description of the data. Giving a function would more accurately describe data that lies on a curve.
What can you say about the correlation coefficient and the correlation description when the points lie exactly on vertical or horizontal line?
Let me rephrase: Case 1: You have x and y variables, but the values for x is a constant (vertical line) Case 1: You have x and y variables, but the values for y is a constant (horizontal line) Result is that you have zero covariance, so a correlation coefficient can not be calculated because that would cause a division by zero. If one of your x value (Case 1) or y value (case 2) is not exactly the same as the others, then a correlation coefficient can be calculated, but does it mean anything? The correlation coefficient indicates a linear relationship between two random variables, not between a constant and a random variable.
What is an example of two variables that would be positively correlated and two variables that could be negatively correlated?
False. Correlation coefficient as denoted by r, ranges from -1 to 1. Coefficient of determination, or r squared ranges from 0 to 1. I note that x,y data points that have a high negative correlation would plot with a negative trend or a negatively sloped line if a best fit regression line is determined. I note also that x,y data points with a high positive correlation would plot with a positive trend or positively sloped line if a best fit regression line is determined. The coefficient of determination for r = 0.9 and r= -0.9 would be 0.81.
What would a correlation of 35 would be called?
An error! Correlation must be between -1 and 1.
A correlation coefficient of 1.36 would be?
impossible
What does a strong negative correlation coefficient mean?
The graph follows a very strong downward trend. Would have helped if you specified which correlation coefficient; there are different types.
When two variables are found to be unrelated the correlation coefficient would be?
Zero.
Which correlation coefficient indicates the weakest relationship between variables?
Pearson's Product Moment Correlation Coefficient indicates how strong the relationship between variables is. A PMCC of zero or very close would mean a very weak correlation. A PMCC of around 1 means a strong correlation.
What is the correlation coefficient to use for ordinal versus nominal data?
I would use Spearman and Kendall
When you removed from the data set how would the correlation coefficient be affected?
If you remove certain data points from a dataset, the correlation coefficient may be affected depending on the nature of the relationship between the removed data points and the remaining data points. If the removed data points have a strong relationship with the remaining data, the correlation coefficient may change significantly. However, if the removed data points have a weak or no relationship with the remaining data, the impact on the correlation coefficient may be minimal.
What value or benefit would a researcher gain by calculating a correlation coeffcient rather than simply describing the relationship as a positive correlation or a negative correlation?
The correlation coefficient gives a measure of the degree to which changes in the variables are related. However, the relationship need not be causal.
What is an example of correlation coefficient?
Correlation coefficient My understanding is: two variables as they relate to one another and how accurately you can predict their behavior to one another when together. Basically the strength of the linear association between two variables. When the variables have a tendency to go up and down together, this is a positive correlation coefficient. Variables with a tendency to go up and down in opposition, (one ends up with a high value and the other a low value) this is negatiove correlation coefficient. An example would be the amount of weight a mom gains during pregnancy and the birth weight of the baby
What type of correlation is one that curved?
Correlation cannot accurately describe any type of curve. The correlation of a curve would be a linear approximation rather than an accurate description of the data. Giving a function would more accurately describe data that lies on a curve.
What can you say about the correlation coefficient and the correlation description when the points lie exactly on vertical or horizontal line?
Let me rephrase: Case 1: You have x and y variables, but the values for x is a constant (vertical line) Case 1: You have x and y variables, but the values for y is a constant (horizontal line) Result is that you have zero covariance, so a correlation coefficient can not be calculated because that would cause a division by zero. If one of your x value (Case 1) or y value (case 2) is not exactly the same as the others, then a correlation coefficient can be calculated, but does it mean anything? The correlation coefficient indicates a linear relationship between two random variables, not between a constant and a random variable.
Is the time elapsed and the number of words typed negative or positive correlation?
It would be a positive correlation. As the time increases, the number of words typed would also increase.
Which of these correlation numbers shows the strongest relationship?
A correlation coefficient of 1 or -1 would be the highest possible statistical relationship. However, the calculation of correlation coefficients between non independent values or small sets of data may show high coefficients when no relationship exists.
