Elaine Eisenbeisz, Owner and Principal Statistician of Omega Statistics, is available for training and workshops in statistics, clinical research, process control/quality assurance, and other topics related to statistics and good research practices. Please call or email the Omega Statistics offices to request the latest brochure and pricing for the event(s) that interests you.
Current offerings and scheduled events are listed below.
In addition to the current offerings listed below, Elaine can design an in-house training or virtual webinar to meet your specific needs. Just give her a call at 951-691-9586 or fill out the contact form on this page to leave her a message and she’ll contact you to schedule a time to discuss your needs and how she can help!

NOTE: In-person events are not being scheduled at this time
Omega Statistics has contracted with 3rd party companies to present the following fee based events. The events are listed in chronological order. Please click on the links that interest you to learn more and to register.

October 22-24, 2025
Learn More About the Biostatistics for the Non-Statistician Seminar
Statistics is a useful decision-making tool in the clinical research arena. When working in a field where a p-value can determine the next steps on development of a drug or procedure, it is imperative that decision makers understand the theory and application of statistics.
Many statistical softwares are now available to professionals. However, these softwares were developed for statisticians and can often be daunting to non-statisticians. How do you know if you are pressing the right key, let alone performing the best test?
This seminar provides a non-mathematical introduction to biostatistics and is designed for non-statisticians. And it will benefit professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.
The focus of the seminar is to give you the information and skills necessary to understand statistical concepts and findings as applies to clinical research, and to confidently convey the information to others.
Emphasis will be placed on the actual statistical (a) concepts, (b) application, and (c) interpretation, and not on mathematical formulas or actual data analysis. A basic understanding of statistics is desired, but not necessary.
(ICH Q Series)
December 3rd and 4th, 2025
Most organizations have programs and procedures but they contain holes or fall short in the implementation of the tools and techniques used to apply proper statistical reasoning and analysis to ICH guidelines. Statistics can help you to better understand, implement, and track processes covered by the ICH guidelines.
This 2-day seminar explores the unique challenges facing quality functions of pharmaceutical and biotechnology companies. Attendees will learn practical implementation solutions as well as best practice descriptions that will allow management to effectively assess, manage and mitigate risk of poorly designed studies. Participants will learn statistical methods related to ICH guidelines and will discover how regulatory agencies, such as the FDA expect organizations to meet these guidelines.
This seminar will provide attendees with an understanding of the fourteen ICH Quality guidelines as relates to statistical guidance and analysis. The course will provide tools, techniques and insight that will allow participants to immediately begin implementation of the information learned within their organization/firm.
March 12, 2026
Learn More About the Applied Time Series Analysis in Healthcare Webinar
Time series models are invaluable to the health care field when it comes to planning and forecasting. Time series models can be used in many aspects of healthcare, including prediction of healthcare expenditures, tracking public health outcomes such as COVID-19, and assessing trends and interventions for patients with hypertension, diabetes, or other chronic diseases.
This 4-hour webinar will provide attendees with the theory and application of time series analysis. The main focus will be on autoregressive integrated moving average (ARIMA) techniques. Variations of the ARIMA and other models which operate under non-linear data, non-stationary data, seasonality, and trends will also be examined.
Examples of times series analyses will be presented using R statistical software. Data and annotated syntax/code will be provided to attendees so they may work the exercises on their own.