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Description

PASS software offers tools for calculating sample sizes across more than 1100 statistical tests and confidence interval scenarios, which is significantly greater than what any other sample size software can provide. Each of these tools has undergone rigorous validation through published research and established texts. You can familiarize yourself with PASS by trying out a free trial, watching the accompanying video, or navigating through this website. With over 25 years of refinement, PASS has established itself as the top choice for sample size software in clinical trials, pharmaceuticals, and various medical research applications. Moreover, it has gained recognition across numerous other domains where sample size assessment is crucial. In just a few simple steps, PASS enables you to determine the sample size required for a statistical test or confidence interval. Should you require assistance at any stage, PASS provides comprehensive documentation, access to free training videos, and the option to reach out to our team of expert Ph.D. statisticians for support. This commitment to user support ensures that all users can effectively utilize the software to meet their research needs.

Description

Introducing an exceptionally user-friendly scoring system specifically designed for small to medium-sized credit institutions, crafted by scoring specialists. This tool delivers precisely what you need for effective real-time scoring, focusing solely on scoring without any outdated, complicated features. It boasts the most favorable cost-to-value ratio available in the industry and can be operational within just a few days. Thanks to its intuitive wizard-based scorecard modeling interface, users find it easy to navigate. You can also monitor and validate scorecards with a selection of pre-defined reports. The system incorporates Reject Inference through both automated and manual methods, alongside automated binning utilizing chi-square techniques and manual binning based on Weight of Evidence (WOE). Additionally, it offers both automatic and manual sampling options, along with graphical statistics to visualize data insights. Users can filter, sort, and reassign portfolio data into “Good” and “Bad” categories, while numeric variables can easily be transformed into categorical forms. Furthermore, it provides correlation coefficients for each variable pair, both before and after the binning process, ensuring comprehensive analysis and understanding of the dataset. With this robust scoring system, credit organizations can enhance their decision-making processes efficiently.