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Description
QDA Miner Lite is a no-cost, user-friendly version of our well-known software designed for computer-assisted qualitative analysis. This tool is ideal for analyzing various types of textual data, including interview transcripts, news articles, and open-ended survey responses, as well as for evaluating still images. Users can easily import documents in formats such as plain text, RTF, HTML, PDF, and data from Excel, MS Access, CSV, and tab-delimited text files. Additionally, it supports the import of data from other qualitative coding programs like Atlas.ti, HyperResearch, and Ethnograph, as well as from transcription software such as Transana and Transcriber, along with Reference Information System (.RIS) files. The software allows users to append comments or memos to coded segments, cases, or entire projects, enhancing the analytical process. Users can retrieve coded data employing Boolean operators (and, or, not) and proximity operators (includes, enclosed, near, before, after) for more precise analysis. Furthermore, tables can be exported in XLS, Tab Delimited, CSV formats, and Word format, making data sharing and reporting more convenient. The interface, along with the help documentation, is available in English, French, and Spanish, ensuring accessibility for a diverse user base. This functionality makes QDA Miner Lite an excellent resource for researchers and analysts looking to streamline their qualitative data analysis.
Description
WizWhy analyzes how the values of one data field are influenced by the values of other fields in the dataset. The analysis hinges on a dependent variable chosen by the user, while the remaining fields act as independent variables or conditions. This dependent variable can be examined in two ways: as a Boolean value or as a continuous measurement.
Users have the ability to refine their analysis by setting various parameters, including the minimum probability for rule formation, the least number of instances required for each rule, and the comparative costs associated with false negatives versus false positives.
WizWhy identifies and presents a series of rules that connect the dependent variable with other fields, expressing these rules using if-then and if-and-only-if constructs. Based on the identified rules, WizWhy highlights significant patterns, reveals unexpected rules that may indicate interesting phenomena, and points out unusual cases within the dataset. Additionally, WizWhy is capable of making predictions for new instances by leveraging the established rules.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
Microsoft Access
Microsoft Excel
Transana
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Provalis Research
Founded
1989
Country
Canada
Website
provalisresearch.com/products/qualitative-data-analysis-software/freeware/
Vendor Details
Company Name
WizSoft
Founded
1983
Country
United States
Website
www.wizsoft.com/products/wizwhy/
Product Features
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
Product 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
