Difference between revisions of "Rules of thumb for interpreting the size of a correlation coefficient"
| Line 32: | Line 32: | ||
Interpreting the line of best fit can show outliers. Outliers can lead to different interpretations of data, and an easy method for spotting outliers is through a scatterplot. | Interpreting the line of best fit can show outliers. Outliers can lead to different interpretations of data, and an easy method for spotting outliers is through a scatterplot. | ||
| − | + | ''contributed by Lauren Moyer'' | |
Revision as of 12:52, 15 December 2019
| Size of positive correlation | Size of negative correlation | Interpretation |
|---|---|---|
| .90 to 1.00 | -.90 to -1.00 | Very high positive (negative) correlation |
| .70 to .90 | -.70 to -.90 | High positive (negative) correlation |
| .50 to .70 | -.50 to -.70 | Moderate positive (negative) correlation |
| .30 to .50 | -.30 to -.50 | Low positive (negative) correlation |
| .00 to .30 | .00 to -.30 | Little, if any, correlation |
contributed by Frank LaBanca EdD
Interpreting the line of best fit can show outliers. Outliers can lead to different interpretations of data, and an easy method for spotting outliers is through a scatterplot.
contributed by Lauren Moyer
