To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject.
To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject.
Solve business problems involving time-to-event and resulting probabilities by following the modeling tutorials in Business Survival Analysis Using SAS(R): An Introduction to Lifetime Probabilities, the first book to be published in the field of business survival analysis!
For SAS programmers or analysts who need to generalize their programs or improve programming efficiency, Art Carpenter thoroughly updates his highly successful second edition of Carpenter's Complete Guide to the SAS Macro Language with an extensive collection of new macro language techniques and examples.
Bridging the gap between statistics texts and SAS documentation, Elementary Statistics Using SAS is written for those who want to perform analyses to solve problems.
SAS/IML software is a powerful tool for data analysts because it enables implementation of statistical algorithms that are not available in any SAS procedure.
This comprehensive resource provides on-the-job training for statistical programmers who use SAS in the pharmaceutical industryThis one-stop resource offers a complete review of what entry- to intermediate-level statistical programmers need to know in order to help with the analysis and reporting of clinical trial data in the pharmaceutical industry.
Query reformulation refers to a process of translating a source query-a request for information in some high-level logic-based language-into a target plan that abides by certain interface restrictions.
