In this comprehensive 4-hour seminar, participants will delve into the core principles and applications of multiple regression, logistic regression, and Cox regression. Designed for professionals across various industries, this training provides a deep understanding of how to model and interpret complex data sets. Learn to apply multiple regression techniques to predict continuous outcomes, use logistic regression for binary outcomes, and employ Cox regression for survival analysis. Through practical examples and interactive sessions, gain the skills necessary to make data-driven decisions and enhance your analytical capabilities. Join us to transform your data analysis approach and unlock powerful insights from your data.
Why Should you Attend:
- Enhance Your Analytical Skills: This seminar provides in-depth training on multiple regression, logistic regression, and Cox regression, equipping you with the essential tools to analyze complex data sets accurately and efficiently.
- Practical Application: Through real-world examples and hands-on exercises, you'll learn to apply these regression techniques to solve practical problems in your field, making the training highly relevant and immediately useful.
- Career Advancement: Gaining proficiency in advanced statistical methods can significantly boost your professional profile, opening up opportunities for career growth and advancement in data-driven roles across various industries.
- Expert Guidance: Learn from an experienced instructor who will provide clear explanations, answer your questions, and offer insights into best practices and common pitfalls in regression analysis.
- Stay Competitive: In today's data-centric world, having advanced data analysis skills is crucial. This training will help you stay ahead of the curve by mastering techniques that are highly valued in the job market.
In-Person Seminar going Virtual with increased learner satisfaction.
Yes, attend this seminar from anywhere. We are making it real and more interactive – Here's a sneak peek:Our enhanced delivery process and technology provides you an immersive experience and will allow you to access:
- The real-time and live presentation as in in-person events
- Private chat for company-specific conversation – the same as you would get in an in-person seminar
- Opportunities to connect with your peers to share knowledge at a different time and have group discussions
- Live workshop activities
- Live Q&A during the event and offline Q&A assistance after the event
- As usual more content, activities and case studies and now adding homework for a comprehensive understanding
- Certification
Learning Objectives:
- Understand the Fundamentals: Gain a solid understanding of multiple regression, logistic regression, and Cox regression, including their underlying assumptions and applications.
- Data Preparation: Learn how to properly prepare and clean data for regression analysis, ensuring accurate and reliable results.
- Model Building: Develop the skills to build and fit regression models using statistical software, including the interpretation of coefficients and other key metrics.
- Results Interpretation: Master the interpretation of regression results, including understanding p-values, confidence intervals, odds ratios, and hazard ratios.
- Diagnostics and Validation: Learn to perform diagnostic checks and validation techniques to assess the goodness-of-fit and robustness of your regression models.
- Communicating Results: Enhance your ability to effectively communicate the results of your regression analyses to non-statistical audiences, including visualizing data and presenting findings clearly.
These learning objectives will ensure that participants leave the seminar with a comprehensive skill set in regression analysis, ready to tackle complex data challenges in their professional roles.
Who will Benefit:
This training program is ideal for individuals seeking to gain expertise in the following topics.
Regression Analysis Seminar, Statistical Methods Training, Data Analysis Techniques, Advanced Statistics Seminar, Online Statistics Course, Multiple Regression Analysis, Logistic Regression Analysis, Cox Regression Analysis, Survival Analysis Techniques, Predictive Modeling Seminar, Biostatistics Training, Clinical Research Analysis, Pharmaceutical Data Analysis, Financial Data Modeling, Market Research Techniques, Environmental Data Analysis, Public Health Data Analysis, Continuing Education in Statistics, Professional Development Seminar, Data Science Skills, Advanced Analytics Training, Career Advancement in Statistics, SPSS Regression Analysis, Training for Data Scientists, Seminar for Statisticians, Healthcare Data Analysis Seminar, Financial Analysts Training, Market Researchers Seminar, Improve Data Analysis Skills, Enhance Predictive Modeling, Understand Regression Techniques, Master Survival Analysis, Advanced Data Analysis Methods
- Healthcare and Medical Research
- Professionals: Biostatisticians, epidemiologists, clinical researchers, medical data analysts.
- Applications: Analyzing patient data, predicting disease outcomes, assessing treatment effectiveness, survival analysis in clinical trials.
- Pharmaceutical Industry
- Professionals: Clinical trial analysts, drug safety specialists, pharmacometricians.
- Applications: Designing and analyzing clinical trials, modeling drug efficacy and safety, regulatory submissions.
- Academia and Research
- Professionals: Researchers, professors, graduate students in fields such as psychology, sociology, and public health.
- Applications: Conducting and publishing quantitative research, analyzing experimental and observational study data.
- Finance and Economics
- Professionals: Financial analysts, econometricians, market researchers.
- Applications: Risk modeling, economic forecasting, market trend analysis, customer behavior prediction.
- Marketing and Market Research
- Professionals: Market analysts, data scientists, consumer insight specialists.
- Applications: Customer segmentation, marketing campaign effectiveness analysis, predictive modeling for sales and customer retention.
- Public Health and Policy Making
- Professionals: Public health analysts, policy advisors, health economists.
- Applications: Evaluating public health interventions, policy impact assessment, health outcomes research.
- Engineering and Technology
- Professionals: Data engineers, software developers, systems analysts.
- Applications: Predictive maintenance, reliability engineering, product lifecycle analysis.
- Environmental Science
- Professionals: Environmental researchers, conservation scientists, ecologists.
- Applications: Environmental impact assessments, species survival analysis, climate change modeling.
- Insurance
- Professionals: Actuaries, risk analysts, underwriting managers.
- Applications: Risk assessment, life insurance modeling, claims prediction.
- Government and Nonprofit Organizations
- Professionals: Policy analysts, program evaluators, social scientists.
- Applications: Program evaluation, policy impact analysis, social research.
- General Benefits
- Skill Enhancement: Provides valuable statistical analysis skills that are widely applicable across various domains.
- Decision Making: Equips professionals with the tools to make data-driven decisions.
- Career Advancement: Enhances the analytical capabilities of professionals, making them more competitive in the job market.
This training will enhance the analytical capabilities of professionals in these fields, enabling them to conduct robust statistical analyses, interpret complex data sets, and make informed decisions based on empirical evidence.
- Introduction and Overview (15 minutes)
- Introduction to the Seminar
- Welcome and objectives
- Brief overview of topics to be covered
- Housekeeping and seminar logistics
- Introduction to the Seminar
- Session 1: Multiple Regression (1 hour)
- Basics of Multiple Regression
- Definition and applications
- Assumptions of multiple regression
- Conducting Multiple Regression Analysis
- Data preparation and exploration
- Running the analysis in statistical software
- Interpreting Results
- Coefficients, significance, and goodness of fit
- Practical examples
- Q&A (10 minutes)
- Basics of Multiple Regression
- Break (10 minutes)
- Session 2: Logistic Regression (1 hour)
- Introduction to Logistic Regression
- When and why to use logistic regression
- Differences from multiple regression
- Conducting Logistic Regression Analysis
- Data requirements and preparation
- Running logistic regression in statistical software
- Interpreting Results
- Odds ratios, coefficients, and model fit
- Case studies and examples
- Q&A (10 minutes)
- Introduction to Logistic Regression
- Break (10 minutes)
- Session 3: Cox Regression (1 hour 15 minutes)
- Understanding Cox Regression
- Introduction to survival analysis
- Kaplan-Meier curves and log-rank test
- Basics of Cox proportional hazards model
- Conducting Cox Regression Analysis
- Data preparation for survival analysis
- Running Cox regression in statistical software
- Interpreting Results
- Hazard ratios and model diagnostics
- Practical examples and case studies
- Q&A (15 minutes)
- Understanding Cox Regression
- Conclusion and Wrap-up (10 minutes)
- Summary of Key Points
- Recap of major topics covered
- Final thoughts and additional resources
- Feedback and Next Steps
- How to apply what was learned
- Further learning opportunities
- Thank you and closing remarks
Elaine Eisenbeisz
Owner, Omega Statistics
Elaine Eisenbeisz is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California. Elaine has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations, to start-up companies and individual researchers.
Elaine’s love of numbers began in elementary school where she placed in regional and statewide mathematics competitions. She attended University of California, Riverside, as a National Science Foundation scholar, where she earned a B.S. in Statistics with a minor in Quantitative Management, Accounting. Elaine received her Master’s Certification in Applied Statistcs from Texas A&M, and is currently finishing her graduate studies at Rochester Institute of Technology. Elaine is a member in good standing with the American Statistical Association as well as many other professional organizations. She is also a member of the Mensa High IQ Society. Omega Statistics holds an A+ rating with the Better Business Bureau.
Elaine has designed the methodology for numerous studies in the clinical, biotech, and health care fields. She currently is an investigator on approximately 10 proton therapy clinical trials for Proton Collaborative Group, based in Illinois. She also designs and analyzes studies as a contract statistician for nutriceutical and fitness studies with QPS, a CRO based in Delaware. Elaine has also worked as a contract statistician with numerous private researchers and biotech start-ups as well as with larger companies such as Allergan and Rio Tinto Minerals. Not only is Elaine well versed in statistical methodology and analysis, she works well with project teams. Throughout her tenure as a private practice statistician, she has published work with researchers and colleagues in peer-reviewed journals. Please visit the Omega Statistics website at www.OmegaStatistics.com to learn more about Elaine and Omega Statistics.
