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3 Day Biostatistics for the Non-Statistician Training Course (January 25-27, 2023)

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Dublin, Dec. 30, 2022 (GLOBE NEWSWIRE) -- The "Biostatistics for the Non-Statistician Training Course" training has been added to ResearchAndMarkets.com's offering.

The objective of this seminar is to provide every trainee with the information and skills that are mandatory to comprehend numerical concepts and answers as smears to scientific study and to positively convey the information to others.

Statistics is a valuable tool that is good and useful for making decisions in the medical research arena. When employed in a field where a p-value can determine the next steps in the development of a drug or procedure, it is authoritative that choice makers comprehend the philosophy and request of statistics.

Quite a few numerical software is now available to professionals. However, this software was industrialized for geometers and can often be unnerving to non-statisticians. How do you know if you are persistent in the right key, let unaided execution be the best test.

This seminar on medical biostatistics online course provides a non-mathematical introduction to biostatistics and is designed for non-statisticians. And it will profit specialists who must comprehend and work with study design and clarification of findings in a scientific or biotechnology setting.

Stress will be placed on the real numerical (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.

The seminar Includes Certificate, PDF copy of the Handouts, Q/A Session, Live Instructor-led 3 Days Web Seminar & Statistical Analysis Plan Template provided by the faculty.

Learning objectives

  • Perform simple analyses in statistical software.

  • Avoid being misinformed by unwise findings.

  • Communicate statistical findings to others more clearly.

  • Comprehend the numerical portions of the greatest articles in medical journals.

  • Do simple calculations, particularly ones that aid in interpreting published literature.

  • Knowledge of which test when, why, and how.

Who Should Attend:

  • Physicians

  • Medical Writers who need to interpret statistical reports

  • Clinical Project Managers/Leaders

  • Clinical Research Associates Sponsors

  • Regulatory Professionals who use statistical concepts/terminology in reporting

  • Clinical research organizations, hospitals, and researchers in health and biotech fields.

  • People engaged in the medical sciences, medicinal and or nutraceutical industries, scientific trials, scientific research, and clinical research administrations, physicians, medicinal students, graduate students in the biological sciences, researchers, and medical writers who need to interpret statistical reports.

Key Topics Covered:

Agenda Day 1: Basics

Session 1: Why Statistics?

  • Do we really need statistical tests?

  • Sample vs. Population

  • I'm a statistician, not a magician!

  • What statistics can and can't do?

  • Descriptive statistics and measures of variability

Session 2: The many ways of interpretation

  • Self-assurance intervals

  • P-values

  • Effect sizes

  • Clinical vs. meaningful significance

Break - 10 mins

Session 3: Types of Data and Descriptive Statistics

  • Levels of data: Incessant, Ordinal, Trifling

  • Normal delivery and its standing

  • Pictorial representations of data

  • Data alterations, when and how

Break 10 mins

Session 4: Common Statistical Tests

  • Relative tests

  • Simple and Manifold reversion examination

  • Non-parametric methods

Q&A

Agenda Day 2: Special Topics

Session 1: Logistic Reversion

  • When and why?

  • Clarification of odd ratios

  • Performance of logistic reversion analysis and clarification

  • Fun with eventuality tables

Session 2: Survival Curves and Cox Regression

  • History, theory, and nomenclature of survival analysis

  • Kaplan-Meier Curves and Log Rank Tests

  • Proportional Hazards

  • Interpretation of hazard ratios

  • Presentation of KM curves and Cox regression analysis and interpretation

Break 10 mins

Session 3: Bayesian Logics

  • A different way of thinking

  • Bayesian methods and statistical significance

  • Bayesian applications to diagnostics testing

  • Bayesian applications to genetics

Break 10 mins

Session 4: Methodical Appraisals and Meta-Analysis

  • Why is doing a methodical review and/or meta-analysis important?

  • A bit of history and reasoning for systematic reviews and/or meta-analysis

  • Vocabulary

  • Steps in performing a Systematic Review

  • Steps in performing a Meta-Analysis

Agenda Day 3: Further Understanding in Clinical Research

Session 1: Other Tests

  • Non-Parametric tests

  • Test for equivalency

  • Test for non-inferiority

Break 10 mins

Session 2: Power and Sample Size

  • Concept, steps, and plans for decisive sample sizes

  • Display of sample size calculations with G-Power software

Session 3: How to Review a Journal Article

  • Overall steps on object evaluation

  • Defining the quality of a periodical or journal article

  • Looking for limitations (all studies have them)

Break 10 mins

Session 4: Developing a Statistical Analysis Plan

  • Using FDA (for the U.S. audience) or MHRA (for the U.K. audience) guidance as a foundation, learn the steps and criteria needed to develop a statistical analysis plan (SAP)

  • An SAP template will be given to all attendees

Key Topics Covered:

Elaine Eisenbeisz
Owner & Principal
Omega Statistics

Elaine Eisenbeisz is aprivate 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 solutionsfor 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.

For more information about this training visit https://www.researchandmarkets.com/r/vkkmhf

About ResearchAndMarkets.com
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