Correlation coefficient

1. a. correlation coefficient
   The correlation coefficient quantifies the degree of relationship between two sets of scores.
2. a. 36.5
   The percentage of variance explained by a correlation coefficient (r) is r². For r = 0.85, r² = 0.7225, which is approximately 72.25%, meaning we know about 27.75% of what we need to know.
3. d. +1.00
   A perfect positive correlation is indicated by a correlation coefficient of +1.00.
4. d. range of scores
   The size of the correlation coefficient can be influenced by the range of scores in the data set.
5. a. correlation matrix
   A correlation matrix systematically represents the correlations between all variables measured in a study.
6. a. either high or low scores
   Adding extreme scores (either high or low) can increase the correlation coefficient.
7. a. correlated
   If candidates score highly on one test and also on another, they are said to be correlated.
8. a. relationship
   The correlation coefficient describes the degree of relationship between two sets of scores.
9. b. 49
   For a correlation coefficient of 0.70, r² = 0.49, indicating we know about 49% of what we need for perfect prediction.
10. d. Spearman rank order
    The Spearman rank order correlation is appropriate for ordinal data.
11. c. negative
    When one variable increases while another decreases, they have a negative correlation.
12. b. measuring the content validity of tests
    Correlation coefficients are not typically used to measure content validity.
13. b. 25%
    If the correlation coefficient is 0.5, then r² = 0.25, indicating that 25% of the variance is shared.
14. b. linear
    The linear correlation can be used to compute the correlation between each item and total test scores.
15. d. subjective
    Subjective criteria tend to yield lower correlations due to variability in interpretation.
16. d. correlation coefficient
    The degree of relationship between two sets of test scores is determined by the correlation coefficient.
17. a. -1.00
    A perfect negative correlation is indicated by a correlation coefficient of -1.00.
18. c. they are measuring similar abilities or skills
    A low correlation might suggest that both tests measure similar constructs but are not identical in their assessment.
19. c. they are tapping the same underlying ability
    A high correlation between very different tests may indicate that they measure similar underlying abilities.
20. a. 0.72
    The maximum possible correlation between two tests is calculated using the formula max=r12×r22max=r12​×r22​​. For reliabilities of 0.64 and 0.81, this results in approximately 0.72.
21. c. Validity is the degree of correlation between two tests.
    Validity refers to how accurately a test measures what it is intended to measure, not merely the correlation between two tests 
22. d. negative correlation
    A negative correlation indicates that higher scores on one variable are associated with lower scores on another variable 
23. b. positive correlation
    A positive correlation occurs when higher scores on one variable are associated with higher scores on another variable 
24. c. correlation coefficient
    The correlation coefficient is a mathematical index that describes both the direction and magnitude of a relationship between two variables