Analyse-it

Analyse-it is a powerful statistical software add-in designed for Microsoft Excel, catering to the needs of users involved in statistical analysis, method validation, and quality control. With over 25 years of development, it has become a trusted tool in more than 12,000 organizations globally, recognized for its robust capabilities and integration with Excel. The software supports five distinct editions tailored for specific use cases: Statistical Research, Quality Control, Medical Research, Method Validation, and an Ultimate Edition that consolidates all features.

Key Functionalities:

• Statistical Analysis: Users can perform advanced statistical hypothesis testing and data analysis, accommodating both continuous numeric and categorical data. This functionality aids in making informed decisions by providing clear insights into datasets.
• Method Validation: Particularly beneficial for laboratories, Analyse-it complies with various regulatory standards and supports Clinical and Laboratory Standards Institute (CLSI) protocols. This ensures accurate validation of measurement systems and diagnostics.
• Quality Control: Tools such as control charts and Pareto analysis help monitor processes and improve quality assurance in manufacturing and medical settings.
• Comprehensive Reporting: The software generates publication-ready reports, enabling users to present data effectively and meet regulatory requirements.
• User-Friendly Interface: The add-in integrates seamlessly with Excel, making it accessible without the need for extensive training. Users have reported significant time savings in their analysis workflows due to its intuitive design.

Target Users:

Analyse-it serves a diverse user base, including healthcare professionals, quality assurance teams, and researchers in various fields. Its adaptability to different needs makes it suitable for industries such as pharmaceuticals, education, and manufacturing.

With continuous updates and extensive customer support, Analyse-it remains committed to enhancing statistical practices in various organizations.