A quick review of steps for Pearson’s r and Scatterplots

Home > A quick review of steps for Pearson’s r and Scatterplots

 









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I. Enter your data into the first two columns in the data file

 

  1. Enter your data for your first variable into the first column of the data file.
  2. Give the first column of data a meaningful name by double clicking on the top of the column. Fill in the ‘variable name’ in the Define Variable box and Click OK.
  3. Enter your data for your second variable into the second column of the data file.
  4. Give the second column of data a meaningful name by double clicking on the top of the column. Fill in the ‘variable name’ in the Define Variable box and Click OK. 
  5. Save the data file to a meaningful place with a meaningful name. This file should have a .sav extension.

II. Analyze your data

 

  1. Click Analyze, Correlate and then Bivariate. A “Bivariate Correlations” box will appear.
  2. Move your first variable to the Variable box by clicking on it to highlight it and clicking on the arrow button.
  3. Move your second variable by clicking on it to highlight it and clicking the arrow button.
  4. Make sure the Pearson box is checked. To check the box, simply click it and a check will appear.
  5. Click OK and wait a few seconds for processing. The output will appear.
  6. Save the output to a meaningful place with a meaningful name. SPSS should give the output file a .spo extension.
  7. While keeping your output file open, go back to the data file to create your scatterplot. Click “Graphs”  and then “Scatter.” A “Scatterplot” Box will appear.
  8. Make sure that the “Simple” selection is selected in the “Scatterplot” Box by clicking it.
  9. Click the “Define” button.
  10. A “Simple Scatterplot” box will appear. Move your first variable to the “Y axis” box by clicking on it to highlight it and moving it with the corresponding arrow button.
  11. Move your second variable to the “X axis” box by clicking on it to highlight it and moving it with the corresponding arrow button.
  12. Click the OK button and wait a few second for processing.
  13. Your scatterplot will appear in your Output file. Save the output file again because it now contains some new information.

 

III. Interpret your results

 

  1. Look in your “Correlations” Box. There will be four quadrants on the right and each will contain numbers. Look for the quadrants that cross your two variables of interest.
  2. Look at the Pearson’s r (Pearson Correlation) value in the appropriate quadrant.
  3. If a Pearson’s r value is positive, you have a positive correlation between your two variables. If a Pearson’s r value is negative, you have a negative correlation between your two variables.
  4. The absolute value of  Pearson’s r will tell you how strong the relationship is between your two variables..
  5. If a Pearson’s r score…
    1. Is close to 0, this means that there is a weak relationship between your two variables.
    2. Is close to 1, this means that there is a strong relationship between your two variables.
  6. Look at the Sig. (2-tailed) value in your “Correlations” table. Some people think this value can tell you if there is a statistically significant correlation between your two variables. Other people think this value is affected to much by the number of observations your make.
  7. If you are one of those people who things that the Sig. (2-tailed) value is important, look at its’ value. If the Sig (2-Tailed) value is greater than 0.05, you can conclude that there is no statistically significant correlation between your two variables. On the other hand, if the Sig (2-Tailed) value is less than 0,05, you can conclude that there is no statistically significant correlation between your two variables.
  8. Look at your scatterplot. Notice if the dots in this plot seem to group together or if they are scattered apart. If the dots appear to group together to form a line, you have a strong correlation between variables. If the dots appear to be random and too scattered, you have a weak correlation between variables.
  9. In your scatterplot, notice how the grouping of your dots slopes. If your dots tend to slope upward from zero, you can conclude that you have a positive correlation between variables. If your dots tend start high from zero and gradually slope down, you can conclude that you have a negative correlation. If the grouping of your dots don’t seem  to slope or if there is no grouping of dots, you have a zero correlation between your variables, aka no correlation.

 

IV. Report your results

 

  1. Report the type of tests used and what they were used to test.
  2. Report the values for Pearson’s r and your Sig. (2-tailed) value if you don’t have a problem with significance testing in correlation . 
  3. Make reference to your scatterplot and include it as a graph in your APA style “Figures” section.
  4. Report your results in words that people can understand.


 

 Background | Enter Data | Analyze Data | Interpret Data | Report Data

 

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