Based on different types of analysis (Refer Section Types of Analysis supported by wizard), different measures are supported in cross-tabs and charts.


Measures supported by Distribution type analysis

To create your distribution analysis and view the measures, Refer Section Distrubution.

The measures supported under this type of analysis are:-

  • Count: This measure can be applied to view the counts of respondents who have answered for the applied side break and top break. Click on Count in your created analysis. The measure will be applied and the new grid will be created in your analysis displaying the counts.  


  • Total%: This shows the Total % of the respondents for the applied side and top breaks. Click on Total% to apply the measure and a new grid will be created in your analysis displaying Total%.

  • Column%: This is a default measure that is shown whenever an analysis is created. This shows the column wise % of your created analysis. To apply or remove this measure, click on Col% and a new grid will be created in your analysis displaying the column%.

  • Row%: This measure can be applied on an analysis to view the Row% of the respondents for the applied side and top breaks. Click on Row% to apply the measure and a new grid will get created in your analysis displaying Row%.


Measures supported by Descriptive Statistics type analysis

For question where the responses are of numeric type like rating questions and numeric type questions, requirement arises to view the mean mode, medians for that numeric data. Although descriptive statistics can also be applied on single choice and multi choice questions in RebusCloud.


To create your distribution analysis and view the measures, Refer Section Descriptive statistics.


Below measures are supported by Descriptive statistics type analysis:-

  • Count: This measure can be applied to view the counts of respondents who have answered for the applied side break and top break. Click on Count in your created analysis. The measure will get applied and new grid will get created in your analysis displaying the counts.

  • Mean: This is the default measure displayed for Descriptive Statistics type analysis. To view the mean scores for your analysis, click on Mean. A new grid will get created in your analysis displaying the Mean score.

  • Mode:To view the Mode scores for your analysis, click on Mode. A new grid will get created in your analysis displaying the Mode. 

  • Median: To view the Median values for your created analysis, click on Median. A new grid will get created in your analysis displaying the Median.

  • Upper Quartile: To view the Upper quartile scores for your created analysis, click on Upper Quartile. A new grid will get created in your analysis displaying the Upper Quartile scores.

Upper Quartile score is basically the median of upper half of the data set. For example: If an an numeric rating question, if the ratings given by the respondents are arranged in ascending order, than upper quartile scores will be calculated on the upper half(lower rated) data of the respondent data set. The median for this upper half of the data set  will become the upper quartile score.

This is used to calculate the interquartile range which is a measure of spread of the middle 50% of the data set which is less affected by outliers.

Each score represented  in the grid/cross-tab for the given side-break and top-break, is the median of the upper half of the data set for the selected measure as upper quartile.


  • Lower Quartile: To view the Lower quartile scores for your created analysis, click on Lower Quartile. A new grid will get created in your analysis displaying the Lower Quartile scores.

Lower Quartile score is the median of the lower half of the data set. For example: If an an numeric rating question, if the ratings given by the respondents are arranged in ascending order, than lower quartile scores will be calculated on the lower half(higher rated) data of the respondent data set. The median for this lower half of the data set will become the lower quartile score. 

This is used to calculate the interquartile range which is a measure of spread of the middle 50% of the data set which is less affected by outliers.

Each score represented  in the grid/cross-tab for the given side-break and top-break, is the median of the lower half of the data set for the selected measure as lower quartile.


Note: Users can apply multiple or all measures at the same time in their analysis.