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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 Quark Analytics?

In a controlled and efficient environment, individuals can quickly extract valuable insights from their datasets. Information can be gathered in a multitude of formats and categories, which facilitates the generation of new variables and allows for the selection of specific cases that pique interest. By employing proficient data analysis methodologies, both quantitative and qualitative variables can undergo extensive examination and scrutiny. The findings may be displayed in either tabular formats or through visual graphics. Furthermore, users have the opportunity to explore the connections between various variables and evaluate the importance of these associations. A range of statistical analyses, including Pearson and Spearman correlations, Chi-Square tests, T-Tests for independent samples, Mann-Whitney tests, ANOVA, and Kruskal-Wallis tests, can be utilized for these evaluations. In addition, selecting and calculating the most frequently used metrics for scale reliability can be done with ease. Consistency across dimensions within the dataset can also be assessed. By applying metrics such as Cronbach's Alpha—both in its raw and standardized forms, with or without the removal of items—alongside Guttman’s six and Intraclass correlation coefficients (ICC), further clarity regarding the reliability of the data is achieved. This thorough methodology not only promotes a detailed comprehension of the data’s framework and interrelations but also enhances the overall quality of the analysis conducted. Ultimately, such rigorous assessment contributes to making informed decisions based on the data insights obtained.

Media

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Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

$29.90/month/user
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

WizSoft

Date Founded

1983

Company Location

United States

Company Website

www.wizsoft.com/products/wizwhy/

Company Facts

Organization Name

Quark Analytics

Date Founded

2019

Company Location

Portugal

Company Website

www.quarkanalytics.com

Categories and Features

Data Analysis

Not specified

Data Mining

Not specified

Predictive Analytics

Not specified

Categories and Features

Data Analysis

Not specified

Statistical Analysis

Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control

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