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A correlation between two variables

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Reference no: EM13523715

TRUE /False  Questions

1. A correlation between two variables does not necessarily that one causes the other. 

2. A standard level for statistical significance is p<.50. 

3. With very large samples, it is possible for a fairly weak relationship to still be statistically significant. 

4. Measurement standardization applies to measurement content, not the administration of measurements. 

5. When numbers are assigned by category, this reflects an ordinal scale of measurement.  

6. If scores are classified as "low", "medium", and high", the scale of measurement is nominal.  

7. Human body weight is an example of a variable measured on a ratio scale of measure. 

8. Numerical employment interview ratings represent objective measures.  

9. Performance appraisal ratings are subjective measures. 

10. The research literature indicates a high correlation between subjective and objective measures of performance. 

11. A correlation score of minus one between two sets of scores indicates an exceptionally low association or relationship between the two sets. 

12. If the correlation coefficient between variables X and Y is .90, this means that the proportion of common variance shared by the two variables is ninety percent. 

13. A correlation coefficient of 1.0 between variables X and Y indicates that there is a perfect linear relationship between these two variables. 

14. The correlation coefficient does not measure the change in one variable caused by another variable. 

15. While correlation is valuable as an indicator of the degree of association between variables, it is generally not used as a tool for prediction. 

16. In staffing the scores of individuals are treated as if they were the attribute itself, rather than merely indicators of the attribute. 

17. The consistency of measurement of an attribute refers to its validity. 

18. Perfect reliability is virtually impossible to achieve because of the presence of measurement error. 

19. Calculation of the test-retest reliability of scores between time periods is done for objective measures, not subjective measures. 

20. Comparing scores of objective measures within the same time period is a measure of internal consistency.

Reference no: EM13523715

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