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What is IBM SPSS Amos?

IBM® SPSS® Amos is a sophisticated software tool designed for advanced structural equation modeling, enhancing traditional multivariate techniques like regression, factor analysis, and correlation analysis. Additionally, it enables users to conduct analysis of variance effectively. With its graphical and programmatic interfaces, you can develop intricate behavioral and attitude models that more precisely depict complex relationships. While Amos comes bundled with the Premium edition of SPSS Statistics, it is offered separately for the Campus edition. Furthermore, Amos can be accessed either as part of SPSS Statistics' base, standard, and professional editions or as an independent application for those who prefer it. This flexibility makes it a valuable resource for researchers and analysts seeking to delve deeper into their data.

What is DataMelt?

DataMelt, commonly referred to as "DMelt," is a versatile environment designed for numerical computations, data analysis, data mining, and computational statistics. It facilitates the plotting of functions and datasets in both 2D and 3D, enables statistical testing, and supports various forms of data analysis, numeric computations, and function minimization. Additionally, it is capable of solving linear and differential equations, and provides methods for symbolic, linear, and non-linear regression. The Java API included in DataMelt integrates neural network capabilities alongside various data manipulation techniques utilizing different algorithms. Furthermore, it offers support for symbolic computations through Octave/Matlab programming elements. As a computational environment based on a Java platform, DataMelt is compatible with multiple operating systems and supports various programming languages, distinguishing it from other statistical tools that often restrict users to a single language. This software uniquely combines Java, the most prevalent enterprise language globally, with popular data science scripting languages such as Jython (Python), Groovy, and JRuby, thereby enhancing its versatility and user accessibility. Consequently, DataMelt emerges as an essential tool for researchers and analysts seeking a comprehensive solution for complex data-driven tasks.

Media

Media

Integrations Supported

IBM SPSS Modeler
IBM SPSS Statistics
icCube

Integrations Supported

Apache NetBeans
Eclipse BIRT

API Availability

API Availability

Has API

Pricing Information

$3,830 per user per month

Pricing Information

$0
Access to full documentation (examples, Java API documentation, online manual) requires one-time membership payment (20$/user)
Free Version

Supported Platforms

SaaS

Supported Platforms

Android
Windows
Mac
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/structural-equation-modeling-sem

Company Facts

Organization Name

jWork.ORG

Date Founded

2005

Company Location

United States

Company Website

datamelt.org

Categories and Features

Statistical Analysis

Not specified

Categories and Features

Artificial Intelligence

For Healthcare
Image Recognition
Machine Learning
Natural Language Processing
Predictive Analytics

Data Analysis

Data Discovery
Data Visualization
Predictive Analytics
Regression Analysis
Statistical Modeling
Text Analytics

Data Mining

Data Extraction
Data Visualization
Machine Learning
Predictive Modeling
Statistical Analysis
Text Mining

Data Visualization

Analytics
Simulation Models
Visual Discovery

Deep Learning

Convolutional Neural Networks
Document Classification
ML Algorithm Library
Model Training
Self-Learning
Visualization

Education

Not specified

Neural Network

Not specified

Statistical Analysis

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

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