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features
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support

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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.

Description

ndCurveMaster, a specialized curve fitting software, is designed to fit curves with multiple variables. It automatically applies nonlinear equations to your datasets. These can be observed or measured values. The software supports curve and surfaces fitting in 2D 3D 4D 5D ..., dimensions. ndCurveMaster is able to handle any data, no matter how complex or how many variables there are. ndCurveMaster, for example, can efficiently derive the optimal equations for a dataset that has six inputs (x1-x6) and a corresponding output Y. For example: Y = a0 - a1 - exp(x1)0.5 + a2 ln(x2)8... + a6 x65.2 to accurately match measured value. ndCurveMaster uses machine learning numerical methods to automatically fit the most suitable nonlinear regression function to your dataset, and discover the relationships between inputs and outputs. This tool supports various curve fitting methods, including linear, polynomial, and nonlinear methods. It also utilizes essential validation and goodness-of-fit tests to ensure accuracy. Additionally, ndCurveMaster provides advanced assessments, such as detecting overfitting and multicollinearity, using tools like the Variance Inflation Factor (VIF) and the Pearson correlation matrix.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Pascal No 
Python No 

Integrations

Pascal Yes 
Python Yes 

Pricing Details

$29.90/month/user
Free Trial Yes 
Free Version No 

Pricing Details

€289
ndCurveMaster WIN/MAC – Web Download
LIFETIME License
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Quark Analytics

Founded

2019

Country

Portugal

Website

www.quarkanalytics.com

Vendor Details

Company Name

SigmaLab Tomas Cepowski

Founded

2017

Country

Poland

Website

www.ndcurvemaster.com

Product Features

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Statistical Analysis

Analytics No 
Association Discovery No 
Compliance Tracking No 
File Management No 
File Storage No 
Forecasting Yes 
Multivariate Analysis Yes 
Regression Analysis Yes 
Statistical Process Control Yes 
Statistical Simulation No 
Survival Analysis No 
Time Series No 
Visualization No 

Product Features

Statistical Analysis

Analytics Yes 
Association Discovery No 
Compliance Tracking No 
File Management No 
File Storage No 
Forecasting Yes 
Multivariate Analysis Yes 
Regression Analysis Yes 
Statistical Process Control Yes 
Statistical Simulation Yes 
Survival Analysis No 
Time Series No 
Visualization Yes 

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