Yes it can be a correlation coefficient.
No, it cannot be a correlation coefficient.
A correlation coefficient is a value between -1 and 1 that shows how close of a good fit the regression line is. For example a regular line has a correlation coefficient of 1. A regression is a best fit and therefore has a correlation coefficient close to one. the closer to one the more accurate the line is to a non regression line.
Evidence that there is no correlation.
A coefficient of zero means there is no correlation between two variables. A coefficient of -1 indicates strong negative correlation, while +1 suggests strong positive correlation.
See Terrell, C. D. (1982). Significance tables for the biserial and point biserial. Educational and Psychological Testing, 42, 975-981.
Dichotomous variables can be either a discrete/true dichotomy or a continuous/artificial one. Examples of discrete dichotomies are male vs female, dead vs alive. There is no underlying continuum between the groups. Continuous or artificial dichotomies are those which we assume there to be an underlying continuum but we assign individuals to a category based on some arbitrary criterion. Examples of this artificial dichotomy are pass vs fail (based on some cutoff score on a test) or short vs tall (based on some arbitrary height). A point-biserial and biserial correlation is used to correlate a dichotomy with an interval scaled variable. The difference is that the point-biserial correlation is used when the dichotomous variable is a true or discrete dichotomy and the biserial correlation is used with an artificial dichotomy.
Yes it can be a correlation coefficient.
No, it cannot be a correlation coefficient.
No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).
The correlation coefficient is symmetrical with respect to X and Y i.e.The correlation coefficient is the geometric mean of the two regression coefficients. or .The correlation coefficient lies between -1 and 1. i.e. .
A correlation coefficient is a value between -1 and 1 that shows how close of a good fit the regression line is. For example a regular line has a correlation coefficient of 1. A regression is a best fit and therefore has a correlation coefficient close to one. the closer to one the more accurate the line is to a non regression line.
A serious error. The maximum magnitude for a correlation coefficient is 1.The Correlation coefficient is lies between -1 to 1 if it is 0 mean there is no correlation between them. Here they are given less than -1 value so it is not a value of correlation coefficient.
the correlation coefficient range is -1 to +1
Evidence that there is no correlation.
The correlation coefficient must lie between -1 and +1 and so a correlation coefficient of 35 is a strong indication of a calculation error. If you meant 0.35, then it is a weak correlation.
A coefficient of zero means there is no correlation between two variables. A coefficient of -1 indicates strong negative correlation, while +1 suggests strong positive correlation.