How to resolve random value generation for hidden characteristics and labels in Spotfire Statistica Data entry

How to resolve random value generation for hidden characteristics and labels in Spotfire Statistica Data entry

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Article ID: KB0070223

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Updated On:

Products

Statistica

Description

Issue Description:

Users may encounter challenges within Statistica Data Entry and the Data Entry Setup (DES) related to hidden characteristics and labels. Users hide these elements in the data entry setup, and as expected, they are not visible on the web data entry page. However, upon creating and saving a new sample, a random hidden value may be unexpectedly generated after exploring the Statistica data entry setup, when it should remain blank. This issue disrupts data accuracy and analysis, impacting the reliability of generated reports.

Root Cause of the Issue:

The root cause of this issue lies in the copying mechanism employed within the Data Entry Setup. When a sample is copied from a source sample that contains hidden characteristics, these hidden values are also copied into the new sample. Consequently, when data entry is completed, these hidden characteristics contribute to the generation of random values within the reports.

Issue/Introduction

In Statistica Data Entry, users sometimes encounter an issue where hidden empty values in the data appear as random values in reports instead of remaining blank. This happens when users copy a source sample to create a new one, unintentionally carrying over hidden values from the original data. This article addresses this issue, which arises when hiding characteristics and labels in the Data Entry setup. It offers guidance on resolving the problem to ensure accurate data representation within Statistica Data Entry.

Environment

Windows

Resolution

To address this issue and prevent the generation of random values in the data configuration, follow these steps: 

1. Avoid Using the Copy Function:

When creating new samples within the TIBCO Statistica DES, refrain from using the copy function, especially when the source sample contains hidden characteristics. 
Instead, manually create a new sample and enter the required data for each new sample to ensure that hidden values are not inadvertently carried over. 

2. Remove Unused Hidden Characteristics/Labels: 

Review the list of hidden characteristics within the Data Entry Setup and identify any that are no longer relevant or in use. These unused hidden characteristics can contribute to the generation of ghost values in the data configuration. Remove these unnecessary hidden characteristics from the Data Entry Setup>>Inputs to streamline data entry processes and minimize the risk of random value generation.