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What is WizWhy?
WizWhy examines the interplay between the values of one data field and those of others within the dataset. This analysis revolves around a user-selected dependent variable, while the other fields serve as independent variables or conditions. The dependent variable can be analyzed in two distinct ways: either as a Boolean value or as a continuous measurement.
To enhance their analysis, users can fine-tune various parameters, such as the minimum probability needed for rule generation, the minimum number of instances required to substantiate each rule, and the relative costs of false negatives compared to false positives.
WizWhy effectively identifies and articulates a set of rules that link the dependent variable to the other fields, employing if-then and if-and-only-if statements to convey these relationships. Furthermore, based on the established rules, WizWhy reveals significant patterns, uncovers unexpected rules that may highlight intriguing phenomena, and identifies anomalies within the dataset. In addition to this, WizWhy can also generate predictions for new instances by utilizing the rules it has derived, enabling users to make informed decisions based on the analysis. The comprehensive insights provided by WizWhy empower users to understand their data more deeply and leverage the findings for strategic purposes.
What is Affect-Tag RX?
Assessing emotions can yield critical insights for objective evaluations. By integrating cognitive data into your consumer and user research, you can make decisions that are based on genuine emotional reactions. The Affect-tag RX solution provides reliable and insightful emotional metrics through a secure web service and a customized dashboard. These metrics are obtained from physiological information collected via the Affect-tag RX mobile application and its unique smartband. This tool is designed for efficient data collection, fitting effortlessly into a variety of research methodologies. Participants can fully engage in their experiences without any potential biases interfering with the outcomes. Furthermore, our unique algorithms analyze physiological data in just a few minutes, granting researchers quick access to impactful insights. This rapid processing empowers researchers to respond promptly to the emotional data gathered, thereby enriching the overall research process and fostering a deeper understanding of consumer behavior. Ultimately, leveraging such technology not only streamlines research but also enhances the quality of insights derived from emotional analyses.
Media
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Integrations Supported
Additional information not provided
Integrations Supported
Additional information not provided
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$1500 per month
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
WizSoft
Date Founded
1983
Company Location
United States
Company Website
www.wizsoft.com/products/wizwhy/
Company Facts
Organization Name
Neotrope
Date Founded
2007
Company Location
France
Company Website
affect-tag.com
Categories and Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Qualitative Data Analysis
Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis
Categories and Features
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Qualitative Data Analysis
Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis