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features
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Description

ChemStat stands out as the most user-friendly and rapid solution for performing statistical evaluations on groundwater monitoring data at RCRA facilities. This application encompasses a wide range of statistical techniques outlined in the 1989 and 1992 USEPA statistical analysis documents, the USEPA Draft Unified Guidance Document, the U.S. Navy Statistical Analysis Guidance document, along with various other recognized guidance and methodologies from esteemed statistical literature. Its remarkable blend of simplicity and cutting-edge technology positions ChemStat as the leading choice for environmental statistical analysis. The constraints on data set size are primarily determined by the computer's memory for the majority of tests, allowing for an extensive array of parameters, wells, and sample dates. Additionally, users can enjoy the flexibility of having limitless parameter names and well label lengths, and they can easily exclude specific data points from their analyses, enhancing the application’s versatility even further. This makes ChemStat an invaluable tool for professionals dealing with complex environmental data.

Description

In a secure and manageable setting, users can swiftly derive insights from their data. Data can be collected in various formats and types, enabling the creation of new variables and the selection of specific cases of interest. Through effective data analysis techniques, both numerical and categorical variables can be thoroughly examined and analyzed. Results can be presented either in tabular form or through graphical representations. Additionally, users can investigate the relationships between different variables and assess the significance of these relationships. Various statistical tests, such as Pearson and Spearman correlations, Chi-Square tests, T-Tests for independent samples, Mann-Whitney, ANOVA, and Kruskal-Wallis, can be employed to achieve this. Moreover, the most commonly used measures of scale reliability can be easily selected and calculated. One can also verify the consistency of dimensions in the dataset. Utilizing measures like Cronbach's Alpha—both raw and standardized, with or without item deletion—Guttman’s six, and Intraclass correlation coefficients (ICC), provides further insights into the reliability of the data. This comprehensive approach ensures a thorough understanding of the data's structure and relationships.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

$990.00
Free Trial
Free Version

Pricing Details

$29.90/month/user
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

Starpoint Software

Website

www.pointstar.com/ChemStat/Default.aspx

Vendor Details

Company Name

Quark Analytics

Founded

2019

Country

Portugal

Website

www.quarkanalytics.com

Product Features

Statistical Analysis

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Statistical Analysis

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization

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