Sometimes a result on a table is different from what you were expecting. A process for tracking down the cause of the results is:
- Check the number of cases in the data set
- Review the sample size for each cell of the table or visualization
- Check filters and weights
- Check the Question Type of the variables used to construct the table
- Review the raw data
- Review value attributes
- Review the inputs and other settings in the object inspector
- Follow links back to their source
- Review Rules
- Review the statistical testing assumptions
- Search Help
- Contact us
Check the number of cases in the data set
A common cause of results that look wrong is that the data file contains too few or too many cases. This is checked by reviewing the Base n shown at the bottom of the page.
Review the sample size for each cell of the table or visualization
Data issues are often discovered by looking at the base n of a table or visualization. (If you can't see the sample size, change the visualization back into a table first.) For example, the visualization below has a sample size of 895 (highlighted in yellow at the bottom).
If you have a visualization, create a table of the input variables and example the n for each cell.
Check filters and weights
If your cell values look wildly off, check the bottom of the page to see if you may have applied a filter or weight.
For example,
See How to Investigate Filters that Show Incorrect or Odd Results or How to Troubleshoot Weights for further help.
Check the Question Type of the variables used to construct the table
When Q imports data it automatically infers the underlying Question Type of the data. These are set automatically when importing data and can be modified in the Variables and Questions tab.
Review the raw data
Select the Data tab at the bottom of the page to review the raw data. Check to see if the values look reasonable. For example, you probably have a problem if you expect to find the values 0 and 1 on the Gender variable but find something else.
Review value attributes
You can see how data has been recoded by selecting any variables and pressing the Values button in the Variables and Questions tab. For example, you could check to see if you unintentionally declared a value missing. If so, that could have a dramatic effect of your results.
Additional insight can be obtained by using the Revert to Source or Split Variables From Question to view the results before the variables were combined.
Review the inputs and other settings in the object inspector
Anything that is calculated in Q - variables, tables, calculations, visualizations - can be clicked on, allowing you to see their data inputs.
Review the statistical testing assumptions
The statistical testing options are set by right-clicking the table and selecting Table Options > Statistical Assumptions. To see more detail on how these settings are applied please see How to Apply Significance Testing in Q
Search Help
The search feature in Q Help (which you are reading at the moment) can be used to search through our documentation. There you may find articles addressing specific issues, such as How to Explain Why Significance Tests Change When I Merge, Hide or Remove Categories
Contact us
If the result looks wrong, and you can't troubleshoot it yourself, please contact support@displayr.com, and give us as much information as you can. Please see the last section in Why Results in Q Are Different to Those From Another Program for tips on how to give us the information that we need to track such things down.
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