The symbolic word for correlation coefficient is:
r
Y
Z
When both variables change in the same direction, then correlation is:
Positive
Negative
Multiple
Constant
The relation existing between income and expenditure is:
Negative correlation
Positive relation
No correlation
No certain relation
Out of the following three measures, which can measure any type of relationship:
Scatter diagram
Spearman's rank correlation
Karl Person's coefficient of correlation
Normal distribution
The other name of rank correlation is:
Karl Pearson's correlation coefficient
Liner relation
Spearman's correlation coefficient
The value of correlation coefficient is always:
More than zero
Between +1 and -1
Less than +1
Less than -1
The following scatter diagram shows that:
Correlation is perfect negative
Correlation is perfect positive
Correlation is low positive
Correlation is low negative
Linear correlation means that the correlation between two variables is:
Perfectly positive
Perfectly Negative
Positive or Negative relation and the degree of relationship between two variables is equal at different levels.
Correlation is zero
Correlation between two or more variables can be:
Positive correlation
Linear correlation
Correlation
If rxy is positive the relation between X and Y is of the type:
When Y increases X increases
When Y decreases X increases
When Y increases X does not change
When Y increases X decreases