Descriptive Analysis Workbook Panelist Performance Counts
What is it?
Why would I use it?
Find out which panelists are able to discriminate between the samples. Identify attributes where further training may be required.
Setup options
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To generate the Panelist Performance Counts sheet, under 2. Select Options, select Panelist performance counts.
Select your lower and upper thresholds.
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- p<=0.25 . Total count of attributes for which the panelist's p-Product is less than or equal to the preset lower threshold.
- 0.25<p<0.5 . Total count of attributes for which the panelist's p-Product is between the preset lower and upper thresholds.
- p>=0.5 . Total count of attributes for which the panelist's p-Product is greater than or equal to the preset upper threshold.
- % of p>=0.5 . The percentage of attributes for which the panelist's p-Product is greater than or equal to the preset upper threshold. The panel average is also provided at the bottom of the column.
- p<=0.25 . Total count of the panelist's p-Product is less than or equal to the preset lower threshold by attribute.
- 0.25<p<0.5 . Total count of the panelist's p-Product is between the preset lower and upper thresholds by attribute.
- p>=0.5 . Total count of the panelist's p-Product is greater than or equal to the preset upper threshold b attribute.
- Panelist name . p-Prod values for each panelist given by attribute.
p-Prod values are calculated from a one-way ANOVA.
Example Conclusion
Based on our threshold criteria, our panel is doing well overall. Tabitha appears to be struggling with the Sweetness Aroma and Sweetness Flavour attributes and we may consider additional training on those attributes for her.
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