Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

AM is a powerful statistical software tool designed specifically for the analysis of data derived from complex samples, particularly for large-scale assessments. With its intuitive drag-and-drop interface, AM combines advanced statistical techniques with user-friendly features, including an integrated help system that guides users through the statistical processes and software navigation. We have prioritized making the installation process straightforward and the software itself easy to operate, though users may still encounter questions or challenges, which this resource aims to address. Currently, AM is in its Beta phase, and the latest Beta Version 0.06.00 introduces significant enhancements to its functionality. For the first time, users can generate statistical graphics, such as bar charts, line charts, and the innovative Sectioned Density Plot, which facilitates the comparison of distributions and represents an evolution from the traditional box-and-whisker plot. We are excited for future updates that will further enrich the graphic capabilities of the software, making it even more versatile for users. This continued development underscores our commitment to providing a robust analytical tool that evolves with user needs.

Description

Statsmodels is a Python library designed for the estimation of various statistical models, enabling users to perform statistical tests and explore data effectively. Each estimator comes with a comprehensive array of result statistics, which are validated against established statistical software to ensure accuracy. This package is distributed under the open-source Modified BSD (3-clause) license, promoting free use and modification. Users can specify models using R-style formulas or utilize pandas DataFrames for convenience. To discover available results, you can check dir(results), and you will find that attributes are detailed in results.__doc__, while methods include their own docstrings for further guidance. Additionally, numpy arrays can be employed as an alternative to formulas. For most users, the simplest way to install statsmodels is through the Anaconda distribution, which caters to data analysis and scientific computing across various platforms. Overall, statsmodels serves as a powerful tool for statisticians and data analysts alike.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Anaconda
Python

Integrations

Anaconda
Python

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
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

American Institutes for Research

Country

United States

Website

am.air.org

Vendor Details

Company Name

statsmodels

Website

www.statsmodels.org/stable/index.html

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

Alternatives

SigmaPlot Reviews

SigmaPlot

Systat Software

Alternatives

CoPlot Reviews

CoPlot

CoHort Software
DataMelt Reviews

DataMelt

jWork.ORG
Aspen Unscrambler Reviews

Aspen Unscrambler

Aspen Technology
Scilab Reviews

Scilab

Scilab Enterprises